The use of logic for knowledge representation and reasoning systems is controversial. There are, indeed, several ways that standard First Order Predicate Logic is inappropriate for modelling natural language understanding and commonsense reasoning. However, a more appropriate logic can be designed. This chapter presents several aspects of such a logic.

Natural language competent embodied cognitive agents should satisfy two requirements. First, they should act in and reason about a changing world, using reasoning in the service of acting and acting in the service of reasoning. Second, they should be able to communicate their beliefs, and report their past, ongoing, and future actions in natural language. This requires a representation of time using a deictic NOW, that models the compositional semantic properties of the English "now". Two problems emerge for an agent that interleaves reasoning and acting in a personal time. The first concerns the representation of plans and reactive rules involving reasoning about "future NOWs". The second emerges when, in the course of reasoning about NOW, the reasoning process itself results in NOW changing. We propose solutions for the two problems and conclude that: (i) for embodied cognitive agents, time is not just the object of reasoning, but is embedded in the reasoning pr...

This paper describes a cognitively plausible computational theory of identifying perceptually indistinguishable objects (PIOs) based on a set of experiments which were designed to identify the knowledge and perceptual cues that people use for this purpose. Identifying a PIO in this context means connecting sensor data from some physical object either to a new mental level symbol or to the correct preexisting one, and is part of the solution to the symbol anchoring problem. We discuss several base cases in the identification process, some related intermediate cases and the knowledge that is needed for the general case. An algorithm for identifying PIOs is included.

of an embodied computational cognitive agent called Cassie, based on the Grounded Layered Architecture with Integrated Reasoning (GLAIR). In this document we describe a new implementation, in which Cassie's body and the world are simulated in Crystal Space, an environment for building 3-D games. We describe the implementation of Cassie in a Crystal Space environment including her current suite of actions and her simulated vision system. Crystal Cassie is a tool for cognitive modeling and testing cognitive theories.

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A cognitive agent is expected to use awareness of the environment and its own body to direct its actions. Such awareness is required for the simplest and most common type of composite acts: sequences. To perform a sequence of acts, a cognitive agent should start performing one step when, and only when, it comes to believe that the previous one has been completed. We present a model for interleaving action, reasoning, and perception in order to allow for the conscious performance of sequences of acts. To define such a model, the notion of act completion needs to be characterized. This is achieved by developing a formal system in which acts are classified along the dimensions of telicity and primitiveness. The proposed system includes and go beyond the traditional binary telic/atelic distinction. 2 1 Introduction Cognitive agents should act consciously. When carrying out a sequence of acts, an agent should be aware of the progression of its acts, and should reason, using it...

Abstract We present a model for error recovery and interrupt handling by a reasoning, acting, and linguistically-competent cognitive agent. Faced with an emergency situation, the agent reasons about what it needs to do and what it is currently doing to decide what to do next. Its reasoning is based on general context-sensitive domain knowledge about the priority of acts. Such knowledge may be provided to the agent in natural language while it is acting, rather than being hardwired into the agent's knowledge base as is the case with most existing systems.

This paper describes "The Trial The Trail" a work of interactive drama for a projection-based virtual reality system. The project marries a virtual reality authoring system and an artificial intelligence system.

We present a solution to McCarthy’s Second Telephone Number Problem. This problem requires an agent to: realize that it lacks some knowledge to complete a task; know the external knowledge sources it can use to obtain the knowledge; know how to obtain the missing knowledge from those sources; actually obtain the missing knowledge; and use the obtained knowledge to complete the task. We explain how a SNePS-based agent solves the problem, and the features of SNePS and the GLAIR architecture that facilitate the solution. These features include: the integration of reasoning and acting; the ability to reason about actions; and the ability to represent and reason about the knowledge contained in external knowledge sources. This latter feature is accomplished through the process of grounding of symbols of the knowledge representation in symbols of an external language.

Anchoring is the process of creating and maintaining the correspondence between symbols and percepts that refer to the same physical objects. This process must necessarily be present in any physically embedded system that includes a symbolic component, for instance, in an autonomous robot that uses a planner to generate strategic decisions.