The work described in this report is motivated by the desire to test the expressive possibilities of action language C+. The Causal Calculator (CCalc) is a system that answers queries about action domains described in a fragment of that language. The Zoo World and the Traffic World have been proposed by Erik Sandewall in his Logic Modelling Workshop—an environment for communicating axiomatizations of action domains of nontrivial size. -/- The Zoo World consists of several cages and the exterior, gates between (...) them, and animals of several species, including humans. Actions in this domain include moving within and between cages, opening and closing gates, and mounting and riding animals. The Traffic World includes vehicles moving continuously between road crossings subject to a number of restrictions, such as speed limits and keeping a fixed safety distance away from other vehicles on the road. We show how to represent the two domains in the input language of CCalc, and how to use CCalc to test these representations. (shrink)

Dynamic epistemic logics provide an account of the evolution of agents’ belief and knowledge when they learn the occurrence of an event. These logics started to become popular about 20 years ago and by now there exists a huge number of publications about them. The present paper briefly summarises the existing body of literature, discusses some problems and shortcomings, and proposes some avenues for future research.

This paper develops Lewis’ notion of convention within a framework that mixes cognitive science with some more social theories of activity like distributed cognition and activity theory. The close examination of everyday situations of convention-based activity will produce some interesting issues for a cognitive theory of behavior. Uncertainty, dynamics, and the complexities of the performance of convention-based activities that are distributed over time and/or place, are driving factors in the analysis that is presented. How the actors reason and manage their (...) collaboration is characterized as pragmatic action. During the course of recurrent activities, the participants adapt previously learned convention-based activities to new circumstances. The coordinating representations that are a part of the design of the context mediate parts of the activity. As they act, the participants learn. (shrink)

This paper presents an approach to artificial intelligence planning based on linear temporal logic (LTL). A simple and easy-to-use planning language is described, Planning Domain Description Language with control Knowledge (PDDL-K), which allows one to specify a planning problem together with heuristic information that can be of help for both pruning the search space and finding better quality plans. The semantics of the language is given in terms of a translation into a set of LTL formulae. Planning is then reduced (...) to “executing” the LTL encoding, i.e. to model search in LTL. The feasibility of the approach has been successfully tested by means of the system Pdk, an implementation of the proposed method. (shrink)

The dominant practice of AI alignment assumes (1) that preferences are an adequate representation of human values, (2) that human rationality can be understood in terms of maximizing the satisfaction of preferences, and (3) that AI systems should be aligned with the preferences of one or more humans to ensure that they behave safely and in accordance with our values. Whether implicitly followed or explicitly endorsed, these commitments constitute what we term a preferentist approach to AI alignment. In this paper, (...) we characterize and challenge the preferentist approach, describing conceptual and technical alternatives that are ripe for further research. We first survey the limits of rational choice theory as a descriptive model, explaining how preferences fail to capture the thick semantic content of human values, and how utility representations neglect the possible incommensurability of those values. We then critique the normativity of expected utility theory (EUT) for humans and AI, drawing upon arguments showing how rational agents need not comply with EUT, while highlighting how EUT is silent on which preferences are normatively acceptable. Finally, we argue that these limitations motivate a reframing of the targets of AI alignment: Instead of alignment with the preferences of a human user, developer, or humanity-writ-large, AI systems should be aligned with normative standards appropriate to their social roles, such as the role of a general-purpose assistant. Furthermore, these standards should be negotiated and agreed upon by all relevant stakeholders. On this alternative conception of alignment, a multiplicity of AI systems will be able to serve diverse ends, aligned with normative standards that promote mutual benefit and limit harm despite our plural and divergent values. (shrink)

Topics in Cognitive Science, Volume 14, Issue 2, Page 327-343, April 2022.

Mīmāṁsā, an Indian hermeneutics provides an exhaustive methodology to interpret Vedic statements. A formalism namely, Mīmāṁsā Inspired Representation of Actions has already been proposed in a preliminary manner. This paper expands the formalism logically and includes Syntax and Semantics covering Soundness and Completeness. Here, several interpretation techniques from Mīmāṁsā have been considered for formalising the statements. Based on these, instructions that denote actions are categorized into positive and prohibitive unconditional imperatives and conditional imperatives that enjoin reason, temporal action and goal. (...) These instructions are evaluated to three values S, V and N. If the instruction is executed with the intention of goal, then it acquires the value of S; if the intention of goal is present and the instruction is not executed, then it assumes the value of V; and if there is no intention of goal, then the instruction is evaluated to N. This formalism has also been applied in different computational settings such as AI planning, Robotics, task analysis and classification of natural language instructions. An outline of these applications and the comparison of this formalism with other relevant theories are also presented in this paper. (shrink)

This paper explores principles governing the rational balance among an agent's beliefs, goals, actions, and intentions. Such principles provide specifications for artificial agents, and approximate a theory of human action (as philosophers use the term). By making explicit the conditions under which an agent can drop his goals, i.e., by specifying how the agent is committed to his goals, the formalism captures a number of important properties of intention. Specifically, the formalism provides analyses for Bratman's three characteristic functional roles played (...) by intentions [7, 9], and shows how agents can avoid intending all the foreseen side-effects of what they actually intend. Finally, the analysis shows how intentions can be adopted relative to a background of relevant beliefs and other intentions or goals. By relativizing one agent's intentions in terms of beliefs about another agent's intentions (or beliefs'), we derive a preliminary account of interpersonal commitments. (shrink)

We address the issue of manipulating games through communication. In the specific setting we consider (a variation of Boolean games), we assume there is some set of environment variables, the values of which are not directly accessible to players; the players have their own beliefs about these variables, and make decisions about what actions to perform based on these beliefs. The communication we consider takes the form of (truthful) announcements about the values of some environment variables; the effect of an (...) announcement is the modification of the beliefs of the players who hear the announcement so that they accurately reflect the values of the announced variables. By choosing announcements appropriately, it is possible to perturb the game away from certain outcomes and towards others. We specifically focus on the issue of stabilisation: making announcements that transform a game from having no stable states to one that has stable configurations. (shrink)

This paper explores the truism that people think about what they say. It proposes that, to satisfy their own goals, people often plan their speech acts to affect their listeners' beliefs, goals, and emotional states. Such language use can be modelled by viewing speech acts as operators in a planning system, thus allowing both physical and speech acts to be integrated into plans. Methodological issues of how speech acts should be defined in a planbased theory are illustrated by defining operators (...) for requesting and informing. Plans containing those operators are presented and comparisons are drawn with Searle's formulation. The operators are shown to be inadequate since they cannot be composed to form questions (requests to inform) and multiparty requests (requests to request). By refining the operator definitions and by identifying some of the side effects of requesting, compositional adequacy is achieved.The solution leads to a metatheoretical principle for modelling speech acts as planning operators. (shrink)

First paper introducing probabilisitic decision theory methods to AI problem solving.

The situation calculus is one of the most established formalisms for reasoning about action and change. In this paper we will review the basics of Reiter’s version of the situation calculus, show how knowledge and time have been addressed in this framework, and point to some of the weaknesses of the situation calculus with respect to time. We then present a modal version of the situation calculus where these problems can be overcome with relative ease and without sacrificing the advantages (...) of the original. (shrink)

The idea that natural language grammar and planned action are relatedsystems has been implicit in psychological theory for more than acentury. However, formal theories in the two domains have tendedto look very different. This article argues that both faculties sharethe formal character of applicative systems based on operationscorresponding to the same two combinatory operations, namely functional composition and type-raising. Viewing them in thisway suggests simpler and more cognitively plausible accounts of bothsystems, and suggests that the language faculty evolved in the (...) speciesand develops in children by a rather direct adaptation of a moreprimitive apparatus for planning purposive action in the world bycomposing affordances of objects or tools. Theknowledge representation that underlies such planning is alsoreflected in the natural language semantics of tense, mood, andaspect, which the paper begins by arguing provides the key tounderstanding both systems. (shrink)