Fodor advocates a view of cognitive processes as computations defined over the language of thought (or Mentalese). Even among those who endorse Mentalese, considerable controversy surrounds its representational format. What semantically relevant structure should scientific psychology attribute to Mentalese symbols? Researchers commonly emphasize logical structure, akin to that displayed by predicate calculus sentences. To counteract this tendency, I discuss computational models of navigation drawn from probabilistic robotics. These models involve computations defined over cognitive maps, which have geometric rather than logical (...) structure. They thereby demonstrate the possibility of rational cognitive processes in an exclusively non-logical representational medium. Furthermore, they offer much promise for the empirical study of animal navigation. (shrink)

This study examines the working memory systems involved in human wayfinding. In the learning phase, 24 participants learned two routes in a novel photorealistic virtual environment displayed on a 220° screen while they were disrupted by a visual, a spatial, a verbal, or—in a control group—no secondary task. In the following wayfinding phase, the participants had to find and to “virtually walk” the two routes again. During this wayfinding phase, a number of dependent measures were recorded. This research shows that (...) encoding wayfinding knowledge interfered with the verbal and with the spatial secondary task. These interferences were even stronger than the interference of wayfinding knowledge with the visual secondary task. These findings are consistent with a dual‐coding approach of wayfinding knowledge. (shrink)

We describe an augmented topological map as an alternative for the proposed bicoded map. Inverting causality, the special nature of the vertical dimension is then no longer fixed a priori and the cause of specific navigation behavior, but a consequence of the combination of the specific geometry of the experimental environment and the motor capabilities of the experimental animals.

One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models. Next we examine evidence that symbolic representations are essential for capturing human cognitive capabilities, drawing on the analogy literature. Then we examine fundamental limitations of feature vectors and other distributed representations that, despite their recent successes on various practical problems, suggest (...) that they are insufficient to capture many aspects of human cognition. After that, we describe the implications for cognitive architecture of our view that analogy is central, and we speculate on roles for hybrid approaches. We close with an analogy that might help bridge the gap. (shrink)

The generation of route descriptions is a fundamental task of navigation systems. A particular problem in this context is to identify routes that can easily be described and processed by users. In this work, we present a framework for representing route networks with the qualitative information necessary to evaluate and optimize route descriptions with regard to ambiguities in them. We identify different agent models that differ in how agents are assumed to process route descriptions while navigating through route networks and (...) discuss which agent models can be translated into PDL programs. Further, we analyze the computational complexity of matching route descriptions and paths in route networks in dependency of the agent model. Finally, we empirically evaluate the influence of the agent model on the optimization and the processing of route instructions. (shrink)

We discuss the important, but greatly under-researched, topic of the social aspects of human wayfinding during navigation. Wayfinding represents the planning and decision-making component of navigation and is arguably among the most common, real-world domains of both individual and group-level decision making. We highlight the myriad ways that wayfinding by people is not a solitary psychological process but is influenced by the actions of other people, even by their mere presence. We also present a novel and comprehensive framework for classifying (...) wayfinding in complex environments that incorporates the influence of other people. This classification builds upon the premises of previous wayfinding taxonomies and is further structured into four parts based upon (1) the nature of the interaction between the actors and (2) the time frame in which the interaction takes place. We highlight gaps in our current understanding of social wayfinding and outline future research opportunities. (shrink)

Mercier & Sperber (M&S) claim that the phenomenon of belief bias provides fundamental support for their argumentative theory and its basis in intuitive judgement. We propose that chronometric evidence necessitates a more nuanced account of belief bias that is not readily captured by argumentative theory.

Mercier & Sperber (M&S) argue for their argumentative theory in terms of communicative abilities. Insights can be gained by extending the discussion beyond human reasoning to rodent and robot navigation. The selection of arguments and conclusions that are mutually reinforcing can be cast as a form of abductive reasoning that I argue underlies the construction of cognitive maps in navigation tasks.

This contribution presents a corpus of spatial descriptions and describes the development of a human-driven spatial language robot system for their comprehension. The domain of application is an eldercare setting in which an assistive robot is asked to “fetch” an object for an elderly resident based on a natural language spatial description given by the resident. In Part One, we describe a corpus of naturally occurring descriptions elicited from a group of older adults within a virtual 3D home that simulates (...) the eldercare setting. We contrast descriptions elicited when participants offered descriptions to a human versus robot avatar, and under instructions to tell the addressee how to find the target versus where the target is. We summarize the key features of the spatial descriptions, including their dynamic versus static nature and the perspective adopted by the speaker. In Part Two, we discuss critical cognitive and perceptual processing capabilities necessary for the robot to establish a common ground with the human user and perform the “fetch” task. Based on the collected corpus, we focus here on resolving the perspective ambiguity and recognizing furniture items used as landmarks in the descriptions. Taken together, the work presented here offers the key building blocks of a robust system that takes as input natural spatial language descriptions and produces commands that drive the robot to successfully fetch objects within our eldercare scenario. (shrink)

Several logical operators are defined as dual pairs, in different types of logics. Such dual pairs of operators also occur in other algebraic theories, such as mathematical morphology. Based on this observation, this paper proposes to define, at the abstract level of institutions, a pair of abstract dual and logical operators as morphological erosion and dilation. Standard quantifiers and modalities are then derived from these two abstract logical operators. These operators are studied both on sets of states and sets of (...) models. To cope with the lack of explicit set of states in institutions, the proposed abstract logical dual operators are defined in an extension of institutions, the stratified institutions, which take into account the notion of open sentences, whose satisfaction is parametrised by sets of states. A hint on the potential interest of the proposed framework for spatial reasoning is also provided. (shrink)

How can an incomplete and uncertain model of the environment be used to perceive, infer, decide and act efficiently? This is the challenge that both living and artificial cognitive systems have to face. Symbolic logic is, by its nature, unable to deal with this question. The subjectivist approach to probability is an extension to logic that is designed specifically to face this challenge. In this paper, we review a number of frequently encountered cognitive issues and cast them into a common (...) Bayesian formalism. The concepts we review are ambiguities, fusion, multimodality, conflicts, modularity, hierarchies and loops. First, each of these concepts is introduced briefly using some examples from the neuroscience, psychophysics or robotics literature. Then, the concept is formalized using a template Bayesian model. The assumptions and common features of these models, as well as their major differences, are outlined and discussed. (shrink)