Learning is a fundamental component of intelligence, and a key consideration in designing cognitive architectures such as Soar [Laird et al., 1986]. This chapter considers the question of what constitutes an appropriate general-purpose learning mechanism. We are interested in mechanisms that might explain and reproduce the rich variety of learning capabilities of humans, ranging from learning p...

This paper provides an overview of the area of psychological inspired symbolic cognitive architectures. It does this by first defining the terms that describe this research area and by selecting three architectures to examine: ACT-R, EPIC, and Soar. For each of these architectures, the motivations, assumptions, and features are evaluated. The similarities and differences between the architectur...

We describe a cognitive model of a collaborative agent that can serve as the basis for automated systems that must collaborate with other agents, including humans, to solve problems. This model builds on standard approaches to cognitive architecture and intelligent agency, as well as formal models of speech acts, joint intention, and intention recognition. The model is nonetheless intended for ...

This paper explores the relationship between dance and language in the light of recent findings from linguistics, cognitive neuroscience and evolutionary psychology. I will argue that at a formal level of sentence construction dance and language share many characteristics, but that the analogy breaks down at the level of meaning, reference, truth and function. With this in mind, I will argue th...

Abstract In this paper we present a brain-inspired cognitive architecture that incorporates sensory processing, classification, contextual prediction, and emotional tagging. The is implemented as three modular web-servers, meaning it can be deployed centrally or across network for servers. experiments reveal two distinct operations of behaviour, namely high- low-salience modes operations, which...

This paper aims to propose and justify a framework for understanding the concept of personhood in both biological artificial entities. The is based on set requirements that make up suitable cognitive architecture an entity be considered person, including ability have propositionally structured intentional states, having form sensory capabilities, means interacting with environment. case individ...

What are the characteristics of long-term learning? We investigated the characteristics of long-term, symbolic learning using the Soar and ACT-R cognitive architectures running cognitive models of two simple tasks. Long sequences of problems were run collecting data to answer fundamental questions about long-term, symbolic learning. We examined whether symbolic learning continues indefinitely, ...

Byrne HoHCI chapter page 2 " Designing interactive computer systems to be efficient and easy to use is important so that people in our society may realize the potential benefits of computer-based tools... Although modern cognitive psychology contains a wealth of knowledge of human behavior, it is not a simple matter to bring this knowledge to bear on the practical problems of design—to build an...

Traditional architectures have fundamental epistemo-logical problems. Perception is inherently resource limited so controlling perception involves all the same AI-complete problems of reasoning about time and resources as the full-scale planing problem. Allowing a planner to transparently assume that the information it needs will automatically be present and up-to-date in the model thus presupp...