Predicting the results of one’s own actions is a powerful cognitive capability that can aid in determining which action to take in a given situation. In this paper, we describe a taskindependent framework based on the Soar cognitive architecture in which rules, episodic memory, semantic memory, mental imagery, and task decomposition are available for predicting an action’s consequences. We incl...

This study explores the utilization of information accidentally accessible in the environment when solving a problem. It contrasts the spontaneous use with the prompted use of such information, i.e. it investigates the relationship between the degree of a priori confidence in the relevance of the information and its efficient use. Three degrees are considered close pragmatic distance (explicit ...

This paper discusses the challenge of designing instructable agents that can learn through interaction with a human expert. Learning through instruction is a powerful paradigm for acquiring knowledge because it limits the complexity of the learning task in a variety of ways. To support learning through instruction, the agent must be able to effectively communicate its lack of knowledge to the h...

The ultimate goal of work in cognitive architecture is to provide the foundation for a system capable of general intelligent behavior. That is, the goal is to provide the underlying structure that would enable a system to perform the full range of cognitive tasks, employ the full range of problem-solving methods and representations appropriate for the tasks, and learn about all aspects of the t...

The broad issue in this paper is the relationship between cognitive psychology and neuroscience. That issue arises particularly sharply for cognitive neurospsychology, some of whose practitioners claim a methodological autonomy for their discipline. They hold that behavioural data from neuropsychological impairments are sufficient to justify assumptions about the underlying modular structure of...

This paper describes how language is grounded by a comprehension system called Lucia within a robotic agent called Rosie that can manipulate objects and navigate indoors. The whole system is built within the Soar cognitive architecture and uses Embodied Construction Grammar (ECG) as a formalism for describing linguistic knowledge. Grounding is performed using knowledge from the grammar itself, ...

The CLARION cognitive architecture has been shown to be capable of simulating and explaining a wide range of psychological tasks and data. Currently, two theories exist to explain the psychological phenomenon of performance degradation under pressure: the distraction theory and the explicit-monitoring theory. However, neither provides a detailed mechanistic explanation of the exact processes in...

What is the role of a cognitive architecture in shaping a model built within it? Compared with a model written in a programming language, the cognitive architecture offers theoretical constraints. These constraints can be “soft”, in that some ways of constructing a model are facilitated and others made more difficult, or they can be “hard”, in that certain aspects of a model are enforced and ot...

Existing models that integrate emotion and cognition generally do not fully specify why cognition needs emotion and conversely why emotion needs cognition. In this paper, we present a unified computational model that combines an abstract cognitive theory of behavior control (PEACTIDM) and a detailed theory of emotion (based on an appraisal theory), integrated in a theory of cognitive architectu...

Integrating language processing, reasoning and decision making is a prerequisite to any breakthroughs in cognitive computing. This paper discusses historical attitudes that have worked against such integration, then describes a cognitive architecture called OntoAgent that illustrates both the feasibility and the payoffs of pursuing integration. Examples are drawn from the Maryland Virtual Patie...