Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this talk, I will show how commonsense reasoning plays a crucial role in this respect. In particular, I will present a cognitively inspired reasoning framework for knowledge invention and creative problem solving exploiting TCL: a non-monotonic extension of a Description Logic (DL) of typicality able to combine prototypical (commonsense) descriptions of concepts in a human-like fashion. (...) The proposed approach has been tested both in the task of goal-driven concept invention and has additionally applied within the context of serendipity-based recommendation systems. I will present the obtained results, the lessons learned, and the road ahead of this research path. (shrink)

Reasoning over our knowledge bases and theories often requires non-deductive inferences, especially – but by no means only – when commonsense reasoning is the case, i.e. when practical agency is called for. This kind of reasoning can be adequately formalized via the notion of supraclassical consequence, a non-deductive consequence tightly associated with default and non-monotonic reasoning and featuring centrally in abductive, inductive, and probabilistic logical systems. In this paper, we analyze core concepts and problems of (...) these systems in the light of supraclassical consequence. (shrink)

Dynamic conceptual reframing represents a crucial mechanism employed by humans, and partially by other animal species, to generate novel knowledge used to solve complex goals. In this talk, I will present a reasoning framework for knowledge invention and creative problem solving exploiting TCL: a non-monotonic extension of a Description Logic (DL) of typicality able to combine prototypical (commonsense) descriptions of concepts in a human-like fashion [1]. The proposed approach has been tested both in the task of goal-driven concept (...) invention [2,3] and has additionally applied within the context of serendipity-based recommendation systems [4]. I will present the obtained results, the lessons learned, and the road ahead of this research path. -/- . (shrink)

In this work we present an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework (i.e. the TCL logic, see Lieto & Pozzato 2020) which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base (see also Lieto et al. 2019, Chiodino et al. 2020 for other applications). In particular, in order to model human-like forms (...) of concept combinations, the TCL logic combines a probabilistic description logics of typicality with the HEAD-MODIFIER heuristics coming from cognitive semantics. In the context of our application of such framework, our system exploits the logic TCL to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik’s theory of emotions, see Plutchik 2001). The generated emotions corresponds to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains. We have tested our system in the context of the H2020 EU project SPICE for providing artistic recommendations of museum items in the Galleria di Arte Moderna (GAM) of Turin. The obtained results (reported in Lieto et al, 2021 and Lieto at al., to appear) show promising results for what concerns both the acceptance of the provided affective recommendation and the explainability associated to each suggestion made by the users. Here we discuss, the open problems and the lessons learned. -/- . (shrink)

Invited Lecture at the SRM ACM Student Chapter, India, on Cognitive Heuristics for Commonsense Thinking and Reasoning in the next generation Artificial Intelligence. The lecture proposes a historical and technical overview of strategies for commonsense reasoning in AI.

This work describes an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework.

I will present two different applications - Dual PECCS and the TCL reasoning framework - addressing some crucial aspects of commonsense reasoning (namely: dealing with typicality effects and with the problem of commonsense compositionality) in a way that is integrated or compliant with different cognitive architectures. In doing so I will show how such aspects are better dealt with at different levels of representation and will discuss the adopted solution to integrate such representational layers.

Fifty years of effort in artificial intelligence (AI) and the formalization of legal reasoning have produced both successes and failures. Considerable success in organizing and displaying evidence and its interrelationships has been accompanied by failure to achieve the original ambition of AI as applied to law: fully automated legal decision-making. The obstacles to formalizing legal reasoning have proved to be the same ones that make the formalization of commonsense reasoning so difficult, and are most evident where (...) legal reasoning has to meld with the vast web of ordinary human knowledge of the world. Underlying many of the problems is the mismatch between the discreteness of symbol manipulation and the continuous nature of imprecise natural language, of degrees of similarity and analogy, and of probabilities. (shrink)

Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning (...) class='Hi'>commonsense categorization and knowledge invention tasks - how cognitively inspired heuristics can help (both in terms of efficiency and efficacy) in the realization of intelligent artificial systems able to reason in a human-like fashion, with results comparable to human-level performances. (shrink)

I accomplish two things in this paper. I explain the motivation for including experimental research in philosophical projects on epistemic reasons and the basing relation. And I present the first experimental contributions to these projects. The results from two experiments advance our understanding of the ordinary concepts of reasons and basing and set the stage for further research on the topics. More specifically, the results support a causal theory of the basing relation, according to which reasons are causes, and a (...) dualist theory of epistemic reasons, according to which reasons include both psychological and non-psychological items. (shrink)

Commonsense reasoning is a crucial human ability employed in everyday tasks. In this talk I provide a knowledge level analysis of the main representational and reasoning problems affecting the cognitive architectures for what concerns this issue. In providing this analysis I will show, by considering some of the main cognitive architectures currently available (e.g. SOAR, ACT-R, CLARION), how one of the main problems of such architectures is represented by the fact that their knowledge representation and processing mechanisms (...) are not sufficiently constrained with insights coming from cognitive science (Lieto 2021; Lieto, Lebiere, Oltramari, 2018). As a possible way out to such knowledge processing issues, I present the main assumptions that have led to the development of the Dual PECCS categorization system (Lieto, Radicioni, Rho 2017) and discuss some of the lessons learned and their possible implications in the design of the knowledge modules and knowledge-processing mechanisms of integrated cognitive architectures. (shrink)

Some research suggests that moral behavior can be strongly influenced by trivial features of the environment of which we are completely unaware. Philosophers, psychologists, and neuroscientists have argued that these findings undermine our commonsense notions of agency and responsibility, both of which emphasize the role of practical reasoning and conscious deliberation in action. We present the results of four vignette-based studies (N = 1,437) designed to investigate how people think about the metaphysical and moral implications of scientific findings (...) that reveal our susceptibility to automaticity and situational influences. When presented with lightly fictionalized narratives about these findings, participants exhibit no tendency toward changing judgments of freedom and responsibility compared to control groups. This suggests that people seem unwilling to adopt skeptical attitudes about agency on the basis of these scientific findings. (shrink)

In this paper we present a framework for the dynamic and automatic generation of novel knowledge obtained through a process of commonsense reasoning based on typicality-based concept combination. We exploit a recently introduced extension of a Description Logic of typicality able to combine prototypical descriptions of concepts in order to generate new prototypical concepts and deal with problem like the PET FISH (Osherson and Smith, 1981; Lieto & Pozzato, 2019). Intuitively, in the context of our application of this (...) logic, the overall pipeline of our system works as follows: given a goal expressed as a set of properties, if the knowledge base does not contain a concept able to fulfill all these properties, then our system looks for two concepts to recombine in order to extend the original knowledge based satisfy the goal. (shrink)

There seem to be many kinds of moral duties. We should keep our promises; we should pay our debts of gratitude; we should compensate those we’ve wronged; we should avoid doing or intending harm; we should help those in need. These constitute, some worry, an unconnected heap of duties: the realm of commonsense morality is a disorganized mess. In this paper, we outline a strategy for unifying commonsense moral duties. We argue that they can be understood in terms (...) of contact with value. You are in contact with a value when you are manifest in it or when it is manifest in you. You have reason to get in contact with the good and avoid contact with evil. And when you’re in contact with a value, the weight of the reasons it grounds are amplified for you. These ideas, we argue, can bring order to the chaos of commonsense morality. (shrink)

Trent Dougherty argues (contra Jonathan Matheson) that when taking into consideration the probabilities involving skeptical theism (ST) and gratuitous evils, an agent may reasonably affirm both ST and that gratuitous evils exist. In other words, Dougherty thinks that assigning a greater than .5 probability to ST is insufficient to defeat the commonsense problem of evil. I argue that Dougherty’s response assumes, incorrectly, that ST functions solely as an evidential defeater, and that, when understood as a closure of inquiry defeater, (...) ST may still defeat reasonable belief in gratuitous evils, even in the face of strong evidence that gratuitous evils exist. (shrink)

We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of the combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC + TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition. We first extend the logic of typicality ALC + TR by typicality inclusions of the (...) form p :: T(C) v D, whose intuitive meaning is that “we believe with degree p about the fact that typical Cs are Ds”. As in the distributed semantics, we define different scenarios containing only some typicality inclusions, each one having a suitable probability. We then exploit such scenarios in order to ascribe typical properties to a concept C obtained as the combination of two prototypical concepts. We also show that reasoning in the proposed Description Logic is EXPTIME-complete as for the underlying standard Description Logic ALC. (shrink)

The success of set theory as a foundation for mathematics inspires its use in artificial intelligence, particularly in commonsense reasoning. In this survey, we briefly review classical set theory from an AI perspective, and then consider alternative set theories. Desirable properties of a possible commonsense set theory are investigated, treating different aspects like cumulative hierarchy, self-reference, cardinality, etc. Assorted examples from the ground-breaking research on the subject are also given.

I will review the main problems concerning commonsense reasoning in machines and I will present resent two different applications - namaly: the Dual PECCS linguistic categorization system and the TCL reasoning framework that have been developed to address, respectively, the problem of typicality effects and the one of commonsense compositionality, in a way that is integrated or compliant with different cognitive architectures thus extending their knowledge processing capabilities In doing so I will show how such aspects (...) are better dealt with at different levels of representation and will discuss how the adoption of a cognitively inspired approach be useful in the design and implementation of the next generation AI systems mastering commonsense. (shrink)

Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this paper, we present TCL (typicality-based compositional logic): a probabilistic, non monotonic extension of standard Description Logics of typicality, and will show how this framework is able to endow artificial systems of a human-like, commonsense based, concept composition procedure that allows its employment in a number of applications (ranging from computational creativity to goal-based reasoning to recommender systems (...) and affective computing). -/- The framework relies on 3 main ingredients: a non monotonic extension of standard Description Logics (allowing to reason on exceptions to inheritance in standard knowledge bases) a probabilistic extension coming from the field of logic programming (the DISPONTE semantics) a cognitive heuristics known ad HEAD-Modifier determining preference rules for the inheritance mechanisms of the novel concepts to be generated via commonsense rules. -/- We report the obtained results and the lessons learned of this research path in the context of model-based AI applications. -/- . (shrink)

In Internal and External Reasons, Bernard Williams proposes a speculative argument for the idea that internal reasons are the only kind of normative reason, and that his counterfactual internal interpretation is the only truth condition for both kinds of reason-statements, H and S (H: “A has a reason to φ” and S: “There is a reason for A to φ”). He takes for granted, however, that internal and external reasons are the only possible kinds of normative reasons at work: his (...) argument is therefore question-begging against a externalism—yet this is only the lesser problem faced by reason internalism. The main problems for Williams’s argument are his semantical reduction of S to H (which entails his question-begging argument) and his ad hoc interpretation of H in terms of his stipulative account of internal reasons. The most serious problem for both reason internalism and reason externalism, however, is represented by certain moral counterintuitive examples on both sides, which could be considered as the central problem in the debate. In this thesis, after showing Williams’s argument to be question-begging, I first explain his failure to unify two irreducible questions (on the nature of normative reasons and on the nature of rationality) as well as to reduce the truth conditions of S to H. Then, through conceptual analysis, I show that William’s internalist interpretation of H is false, and that the commonsensical interpretation of H is one that I call contextual interpretation in terms of contextual reasons. Internal reasons are just one usage of H, and contextual reasons are the real rival to external reasons in the debate on normative reason. Secondly, I argue that the two distinct notions of rationality— relative (instrumental) rationality and absolute rationality—require two distinct truth conditions, and the central problem deals only with the absolute one. I hope to show that reason contextualism, defined in terms of contextual reasons (i.e., neither internal nor external reasons) provides us with the best explication of these two distinct notions of rationality, and that the contextual interpretation accommodates all the counterexamples associated with the central problem. (shrink)

For a symposium on Douglas W. Portmore's Commonsense Consequentialism: Wherein Morality Meets Rationality.

This paper investigates an alternative set theory (due to Peter Aczel) called Hyperset Theory. Aczel uses a graphical representation for sets and thereby allows the representation of non-well-founded sets. A program, called HYPERSOLVER, which can solve systems of equations defined in terms of sets in the universe of this new theory is presented. This may be a useful tool for commonsense reasoning.

The notion of Simulative Reasoning in the study of propositional attitudes within Artificial Intelligence (AI) is strongly related to the Simulation Theory of mental ascription in Philosophy. Roughly speaking, when an AI system engages in Simulative Reasoning about a target agent, it reasons with that agent’s beliefs as temporary hypotheses of its own, thereby coming to conclusions about what the agent might conclude or might have concluded. The contrast is with non-simulative meta-reasoning, where the AI system reasons (...) within a detailed theory about the agent’s (conjectured) reasoning acts. The motive within AI for preferring Simulative Reasoning is that it is more convenient and efficient, because of a simplification of the representations and reasoning processes. The chapter discusses this advantage in detail. It also sketches the use of Simulative Reasoning in an AI natural language processing system, ATT-Meta, that is currently being implemented. This system is directed at the understanding of propositional attitude reports. In ATT-Meta, Simulative Reasoning is yoked to a somewhat independent set of ideas about how attitude reports should be treated. Central here are the claims that (a) speakers often employ commonsense (and largely metaphorical) models of mind in describing agents’ attitudes, (b) the listener accordingly needs often to reason within the terms of such models, rather than on the basis of any objectively justifiable characterization of the mind, and (c) the commonsense models filter the suggestions that Simulative Reasoning comes up with concerning target agents’ reasoning conclusions. There is a yet tighter connection between the commonsense models and the Simulative Reasoning. It turns out that Simulative Reasoning can be rationally reconstructed in terms of a more general type of reasoning about the possibly-counterfactual “world” that the target agent believes in, together with an assumption that that agent has a faithful representation of the world. In the ATT-Meta approach, the reasoner adopts that assumption when it views the target agent through a particular commonsense model (called IDEAS-AS-MODELS). (shrink)

Empirical evidence challenges many of the assumptions that underlie traditional philosophical and commonsense conceptions of human agency. It has been suggested that this evidence threatens also to undermine free will and moral responsibility. In this paper, I will focus on the purported threat to moral responsibility. The evidence challenges assumptions concerning the ability to exercise conscious control and to act for reasons. This raises an apparent challenge to moral responsibility as these abilities appear to be necessary for morally responsible (...) agency. I will argue that this challenge collapses once the underlying conditions on moral responsibility are specified in sufficient detail. I will argue, in other words, that the empirical evidence does not support a challenge to the assumption that we are, in general, morally responsible agents. In the final section, I will suggest that empirical research on human agency is nevertheless relevant to various questions about moral responsibility. (shrink)

According to Agnosticism with a capital A, even if we don’t see how any reason we know of would justify God in permitting all the evil in the world and even if we lack evidential and non-evidential warrant for theism, we should not infer that there probably is no reason that would justify God. That’s because, under those conditions, we should be in doubt about whether the goods we know of constitute a representative sample of all the goods there are, (...) among relevantly similar things. In my "Epistemic Humility, Arguments from Evil, and Moral Skepticism" (2009), I defended Agnosticism against the charge that it leaves us in doubt about whether we are obligated to intervene to prevent horrific suffering we can prevent at no risk to ourselves. In his “Agnosticism, Skeptical Theism, and Moral Obligation” (2014), Stephen Maitzen argues that, in light of my defense, Agnosticism is at odds with commonsense morality’s insistence that we have an obligation to intervene in such cases. In the present essay, I argue that the moral principle Maitzen seems to impute to commonsense (it's hard to tell what principle he has in mind) is false and that a moral principle much more in keeping with commonsense is compatible with Agnosticism and my defense of it. Along the way, I mention multiple misrepresentations Maitzen makes of Agnosticism and my defense of it. (shrink)

Exclusionary defeat is Joseph Raz’s proposal for understanding the more complex, layered structure of practical reasoning. Exclusionary reasons are widely appealed to in legal theory and consistently arise in many other areas of philosophy. They have also been subject to a variety of challenges. I propose a new account of exclusionary reasons based on their justificatory role, rejecting Raz’s motivational account and especially contrasting exclusion with undercutting defeat. I explain the appeal and coherence of exclusionary reasons by appeal to (...) commonsense value pluralism and the intermediate space of public policies, social roles, and organizations. We often want our choices to have a certain character or instantiate a certain value and in order to do so, that choice can only be based on a restricted set of reasons. Exclusion explains how pro tanto practical reasons can be disqualified from counting towards a choice of a particular kind without being outweighed or undercut. (shrink)

Regard for Reason in the Moral Mind argues that a careful examination of the scientific literature reveals a foundational role for reasoning in moral thought and action. Grounding moral psychology in reason then paves the way for a defense of moral knowledge and virtue against a variety of empirical challenges, such as debunking arguments and situationist critiques. The book attempts to provide a corrective to current trends in moral psychology, which celebrate emotion over reason and generate pessimism about the (...) psychological mechanisms underlying commonsense morality. Ultimately, there is rationality in ethics not just despite but in virtue of the neurobiological and evolutionary materials that shape moral cognition and motivation. (shrink)

In his 2013 book, “Moral Tribes: Emotion, Reason, and the Gap between Us and Them,” Joshua Greene1 contemplates two tragedies. The first is the tragedy of the commons, a well- studied problem in the game theory and psychology literature. Here, if people are truly self- interested, cooperation cannot arise, and everyone will use the commons until it is depleted. This problem is succinctly called the “Me vs. Us” problem. The second is the tragedy of the commonsense morality, which Greene (...) named, refers to the problem of cooperation among groups, the “Us vs. Them” problem. (shrink)

Psychoanalytic reasoning is an instance of inference to the best explanation and provides an extension of commonsense psychology that is potentially cogent, cumulative, and radical.

Commonsense reasoning about the physical world, as exemplified by "Iron sinks in water" or "If a ball is dropped it gains speed," will be indispensable in future programs. We argue that to make such predictions (namely, envisioning), programs should use abstract entities (such as the gravitational field), principles (such as the principle of superposition), and laws (such as the conservation of energy) of physics for representation and reasoning. These arguments are in accord with a recent study in (...) physics instruction where expert problem solving is related to the construction of physical representations that contain fictitious, imagined entities such as forces and momenta (Larkin 1983). We give several examples showing the power of physical representations. (shrink)

Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this lecture, I will present the TCL reasoning framework that has been developed to address the problem of dynamic, goal-directed, knowledge invention and will show how it has been applied to different case studies and applications in the areas of (...) cognitive robotics, cognitive architectures and computational creativity. (shrink)

Many people presume that you can permissibly support the good features of a symbol, person, activity, or work of art while simultaneously denouncing its bad features. This chapter refines and assesses this commonsense (but undertheorized) moral justification for supporting problematic people, projects, and political symbols, and proposes an analogue of the Doctrine of Double Effect called the Doctrine of Double Endorsement (DDN). DDN proposes that when certain conditions are met, it is morally permissible to directly endorse some object in (...) virtue of its positive properties while standing against its negative properties, even though it would be morally impermissible to directly endorse those negative properties themselves. These conditions include separability (the good and bad features must not be inextricably linked), proportionality (the positive value of the good features must be significantly greater than the negative value of the bad features), and constrained choice (there must not be other things that the agent could endorse instead that share the same positive features but are not saddled with the negative ones). The chapter applies these constraints to a number of practical issues, including (among others) voting for morally troubling candidates, supporting Confederate monuments, and consuming sexist art. (shrink)

The field of AI has undergone a series of transformations, each marking a new phase of development. The initial phase emphasized curation of symbolic models which excelled in capturing reasoning but were fragile and not scalable. The next phase was characterized by machine learning models—most recently large language models (LLMs)—which were more robust and easier to scale but struggled with reasoning. Now, we are witnessing a return to symbolic models as complementing machine learning. Successes of LLMs contrast with (...) their inscrutability, inaccuracy, and hallucinations, which underwrite concerns over the reliability and trustworthiness of these systems, motivating investigations into commonsense reasoning, AI explainability, and formal verification techniques. Moreover, proper assessments of hybrid machine learning/symbolic systems require novel strategies to facilitate comparisons of performance and guide future AI progress. The EDGeS AAAI 2023 Spring symposium brought together researchers focusing on novel assessments and benchmarks for evaluating hybrid and artificial general intelligence (AGI) systems. This symposium revealed what was already suspected: research concerning evaluation of machine learning/symbolic hybrids and AGI is, unfortunately, lacking. Even so, the discussion was fruitful. (shrink)

My aim is to propose a better way to understand moral demandingness: a counterfactual view that requires us to consider the demands that moral theories make across other possible worlds. Seemingly, the demandingness of any moral theory or principle should be evaluated in terms of that theory’s general demandingness. This, in turn, implies that we ought to be concerned about the possible demandingness of moral theories and not just about how demanding they actually are. This counterfactual view might also have (...) some surprising implications about how demanding commonsense morality really is. After all, commonsense morality might be extremely demanding in many possible worlds. This consideration, in turn, risks undermining the commonsense moral theorist's ability to make purely cost-based demandingness objections against consequentialism, giving us strong reasons to worry about the purely cost-based demandingness objection’s viability in general. (shrink)

A logical formalization of emotions is considered to be tricky because they appear to have no strict types, reasons, and consequences. On the other hand, such a formalization is crucial for commonsense reasoning. Here, the so-called "object directedness" of emotions is studied by using Helen Nissenbaum's influential ideas.

This paper presents a practical case study showing how, despite the nowadays limited collaboration between AI and Cognitive Science (CogSci), cognitive research can still have an important role in the development of novel AI technologies. After a brief historical introduction about the reasons of the divorce between AI and CogSci research agendas (happened in the mid’80s of the last century), we try to provide evidence of a renewed collaboration by showing a recent case study on a commonsense reasoning (...) system, built by using insights from cognitive semantics. (shrink)

In this work we present NERVOUS, an intelligent recommender system exploiting a probabilistic extension of a Description Logic of typicality to dynamically generate novel contents in AllMusic, a comprehensive and in-depth resource about music, providing data about albums, bands, musicians and songs. The tool can be used for both the generation of novel music genres and styles, described by a set of typical properties characterizing them, and the reclassification of the available songs within such new genres.

It is a widely held view that lying is defined in the traditional tripartite model as the conjunction of a statement, the false belief, and the intended deception. Much of the criticisms have been levelled at the third condition—intended deception—with contemporary counterexamples. My main criticism of the traditional and contemporary model of lying centres on that philosophers discard the social existence of the hearer. Schutz‘s phenomenological sociology gives a sheer inspiration to redefine the third condition by taking the hearer as (...) a consciously social being into account. Lying should be an intersubjective action for the Other from the perspective of the liar; it might be, thus, reasonable to assume that there should be commonsense awareness between the speaker and the hearer. This paper, by focusing on this commonsenseness and its typifications, introduces a new approach to the third condition: S must intend that H be induced to believe that p, where p is false. In this regard, once you lie, by being subjected to the taken-for-granted commonsenseness in our daily life, you must try as hard as possible to succeed in deceiving the hearer by stating that p. You, as a typical person, tell a typical lie in typical contexts for typical Others. The focus of attention, therefore, is on the hearer and it is the key to understanding that mere intent to deceive is too broad and unpragmatic for a social human being who always intends to flee the negative consequences of the context in which she has to lie. Making the extension narrower necessitates a new term, anti-social bullshit generally being replied rhetorically as "how can you expect me to believe that?" comprises the excluded cases. (shrink)

Formalizing commonsense knowledge for reasoning about time has long been a central issue in AI. It has been recognized that the existing formalisms do not provide satisfactory solutions to some fundamental problems, viz. the frame problem. Moreover, it has turned out that the inferences drawn do not always coincide with those one had intended when one wrote the axioms. These issues call for a well-defined formalism and useful computational utilities for reasoning about time and change. Yoav Shoham (...) of Stanford University introduced in his 1986 Yale doctoral thesis an appealing temporal nonmonotonic logic and identified a class of theories, causal theories, which have computationally simple model-theoretic properties. This paper is a study towards building upon Shoham's work on causal theories. We concentrate on improving computational aspects of causal theories while preserving their model-theoretic properties. (shrink)

The Authority Account provides a new explanation why commonsense morality contains prudential options—options that permit agents to perform actions that promote their own wellbeing more than the action they have most reason to do, from the moral point of view. At the core of that explanation are two claims. The first is that moral requirements are traditionally widely taken to have an authoritative status; that is, to be rules that morality imposes by right. The second is that in order (...) for moral requirements to have such a status, morality must contain prudential options. If both of these claims are true, then they will create a pressure to think of morality as containing prudential options. And according to the Authority Account, the fact that commonsense morality contains such options is the result of this pressure. (shrink)

In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for (...) the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures. (shrink)

Moorean arguments are a popular and powerful way to engage highly revisionary philosophical views, such as nihilism about motion, time, truth, consciousness, causation, and various kinds of skepticism (e.g., external world, other minds, inductive, global). They take, as a premise, a highly plausible first-order claim (e.g., cars move, I ate breakfast before lunch, it’s true that some fish have gills) and conclude from it the falsity of the highly revisionary philosophical thesis. Moorean arguments can be used against nihilists in ethics (...) (error theorists), too. Recently, error theorists have recognized Moorean arguments as a powerful challenge and have tried to meet it. They’ve argued that moral Moorean premises seem highly credible to us, but aren’t, by offering various debunking explanations. These explanations all appeal to higher-order evidence—evidence of error in our reasoning. I argue that drawing attention to higher-order evidence is a welcome contribution from error theorists, but that the higher-order evidence actually counts further against error theoretic arguments—including their debunking explanations—and further in favor of Moorean arguments and the commonsense views they support. Along the way I answer a few prominent objections to Moorean arguments: that they are objectionably question-begging, rely on categorizing some facts as “Moorean Facts”, and that reports of one’s credence in a proposition bears no interesting relation to that proposition’s credibility. (shrink)

Agnieszka Jaworska and Julie Tannenbaum recently developed the ingenious and novel person‐rearing account of moral status, which preserves the commonsense judgment that humans have a higher moral status than nonhuman animals. It aims to vindicate speciesist judgments while avoiding the problems typically associated with speciesist views. We argue, however, that there is good reason to reject person‐rearing views. Person‐rearing views have to be coupled with an account of flourishing, which will (according to Jaworska and Tannenbaum) be either a species (...) norm or an intrinsic potential account of flourishing. As we show, however, person‐rearing accounts generate extremely implausible consequences when combined with the accounts of flourishing Jaworska and Tannenbaum need for the purposes of their view. (shrink)

Partiality is the special concern that we display for ourselves and other people with whom we stand in some special personal relationship. It is a central theme in moral philosophy, both ancient and modern. Questions about the justification of partiality arise in the context of enquiry into several moral topics, including the good life and the role in it of our personal commitments; the demands of impartial morality, equality, and other moral ideals; and commonsense ideas about supererogation. This paper (...) provides an overview of the debate on the ethics of partiality through the lens of the domains of permissible and required partiality. After outlining the conceptual space, I first discuss agent-centred moral options that concern permissions not to do what would be impartially optimal. I then focus on required partiality, which concerns associative duties that go beyond our general duties to others and require us to give special priority to people who are close to us. I discuss some notable features of associative duties and the two main objections that have been raised against them: the Voluntarist and the Distributive objections. I then turn to the justification of partiality, focusing on underivative approaches and reasons-based frameworks. I discuss the reductionism and non-reductionism debate: the question whether partiality is derivative or fundamental. I survey arguments for ‘the big three’, according to which partiality is justified by appeal to the special value of either projects, personal relationships, or individuals. I conclude by discussing four newly emerging areas in the debate: normative transitions of various personal relationships, relationships with AI, epistemic partiality, and negative partiality, which concerns the negative analogue of our positive personal relationships. (shrink)

According to what Birch (2022) calls the theory-heavy approach to investigating nonhuman-animal consciousness, we select one of the well-developed theories of consciousness currently debated within contemporary cognitive science and investigate whether animals exhibit the neural structures or cognitive abilities posited by that theory as sufficient for consciousness. Birch argues, however, that this approach is in general problematic because it faces what he dubs the dilemma of demandingness—roughly, that we cannot use theories that are based on the human case to assess (...) consciousness in nonhuman animals and vice versa. We argue here that, though this dilemma may problematize the application of many current accounts of consciousness to nonhuman animals, it does not challenge the use of standard versions of the higher-order thought theory (“HOTT”) of consciousness, according to which a creature is in a conscious mental state just in case it is aware of being in that state via a suitable higher-order thought (“HOT”). We show this in two ways. First, we argue that, unlike many extant theories of consciousness, HOTT is typically motivated by a commonsense, and more importantly, neutral condition on consciousness that applies to humans and animals alike. Second, we offer new empirical and theoretical reasons to think that many nonhuman animals possess the relevant HOTs necessary for consciousness. Considering these issues not only reveals the explanatory power of HOTT and some of its advantages over rival accounts, but also enables us to further extend and clarify the theory. (shrink)

Galen Strawson’s Basic Argument is that because self-creation is required to be truly morally responsible and self-creation is impossible, it is impossible to be truly morally responsible for anything. I contend that the Basic Argument is unpersuasive and unsound. First, I argue that the moral luck debate shows that the self-creation requirement appears to be contradicted and supported by various parts of our commonsense ideas about moral responsibility, and that this ambivalence undermines the only reason that Strawson gives for (...) the self-creation requirement. Second, I argue that the self-creation requirement is so demanding that either it is an implausible requirement for a species of true moral responsibility that we take ourselves to have or it is a plausible requirement of a species of true moral responsibility that we have never taken ourselves to have. Third, I explain that Strawson overgeneralizes from instances of constitutive luck that obviously undermine moral responsibility to all kinds of constitutive luck. (shrink)

It is often called “the problem of free will and determinism,” as if the only thing that might challenge free will is determinism and as if determinism is obviously a problem. The traditional debates about free will have proceeded accordingly. Typically, incompatibilists about free will and determinism suggest that their position is intuitive or commonsensical, such that compatibilists have the burden of showing how, despite appearances, the problem of determinism is not really a problem. Compatibilists, in turn, tend to proceed (...) as if showing that determinism is not a problem thereby shows that we have free will, as if determinism is the only thing that might threaten free will. In this chapter, I reject both of these elements of the traditional debate; the question of whether we have free will should neither begin nor end with the so-called problem of determinism. I present and discuss evidence from a variety of studies that suggests that incompatibilism is not particularly intuitive. Most people do not have to be talked out of incompatibilism but rather talked into it. This provides some reasons—though certainly not decisive reasons—to think that compatibilism is true. I conclude by pointing out that, even if compatibilism were true, it would not dissolve the problem of free will, because there are problems other than determinism that need to be confronted—namely, challenges to free will suggested by current and “future science,” including neuroscience and psychology. The threats to free will suggested by these sciences are distinct from the traditional threat of determinism, and they are the ones that “ordinary persons” find intuitively threatening to free will. In fact, I will argue that the reason incompatibilism about free will and determinism appears to be intuitive is that determinism is often and easily misunderstood to involve these distinct threats to free will—threats that suggest that our rational, conscious mental activity is bypassed in the process of our making decisions and coming to act. (shrink)

Most ordinary folks think that there are ordinary objects such as trees and frogs. They do not think there are extraordinary objects such as the mereological sum of trees and frogs, as the permissivist does. Nor do they deny the existence of ordinary composite objects such as tables, as the eliminativist does. In his recent book, Objects: Nothing Out of the Ordinary, Korman positions himself alongside ordinary folk. He deftly defends the common sense view of ordinary objects, and argues against (...) the permissivist and eliminativist. One of the ways he does this is by launching what he calls ‘arguments from counterexample’. In this paper, I focus on the dialectical effectiveness of such arguments generally. I discuss whether and how we might sometimes be justified in using arguments from counterexample and commonsense in philosophical debate, even if they appear to be (or are) question-begging. I conclude that, given some of Korman’s other commitments, there is little reason for his opponents to take his arguments from counterexample seriously. (shrink)

Philosophers from Hart to Lewis, Johnston and Bennett have expressed various degrees of reservation concerning the doctrine of double effect. A common concern is that, with regard to many activities that double effect is traditionally thought to prohibit, what might at first look to be a directly intended bad effect is really, on closer examination, a directly intended neutral effect that is closely connected to a foreseen bad effect. This essay examines the extent to which the commonsense concept of (...) intention supports a reasonably consistent and coherent application of double effect. Two important conclusions are these: (1) a number of traditionally proscribed activities involve a kind of “targeting” of innocents that can be taken to exhibit a direct intention to harm them; (2) a direct intention to harm need not involve a desire to harm in any ordinary sense of the latter expression. (shrink)