ABSTRACT: Affect is considered by most contempo-rary theories to be postcognitive, that is, to occur only after considerable cognitive operations have been ac-complished. Yet a number of experimental results on preferences, attitudes, impression formation, and de-_ cision making, as well as some

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Introspection or the ability to observe one's own behavior is one of the most powerful capabilities of human intelligence; it is the basis for understanding and improvement of one's behavior and of human progress. Similarly, introspective computer systems, introduced in this thesis

Introduction Cooperative Distributed Problem-Solving (CDPS) studies how a loosely-coupled network of problem solvers can work together to solve problems that are beyond their individual capabilities. Each problem-solving node in the network is capable of sophisticated problem solving and can work independently, but the problems faced by the nodes cannot be completed without cooperation. Cooperation is necessary because no single node has sufficient expertise, resources, and information to solve a problem, and different nodes might have expertise for solving different parts of the problem. For example, if the problem is to design a house, one node might have expertise on the strength of structural materials, another on the space requirements for different types of rooms, another on plumbing, another on electrical wiring, and so on. Different nodes might have different resources: some might be very fast at computation, others might have connections that speed communication, whil

focuses upon the latter topic: self assessment. This thesis develops a framework called robotic introspection to provide a self-assessment mechanism for field-capable robots. Robotic introspection models and monitors operational

the mechanisms of human social cognition in order to build relationships in the most natural manner possible. People build

Lexical-semantic resources, including thesauri and WORDNET, have been successfully incorporated into a wide range of applications in Natural Language Processing. However they are very difficult and expensive to create and maintain, and their usefulness has been severely hampered by their limited coverage, bias and inconsistency. Automated and semi-automated methods for developing such resources are therefore crucial for further resource development and improved application performance.

Are ‘‘implicit’ ’ attitudes unconscious? q a, * b a

This book introduces ontological semantics, a comprehensive approach to the treatment of text meaning by computer. Ontological semantics is an integrated complex of theories, methodologies, descriptions and implementations. In ontological semantics, a theory is viewed as a set of statements determining the format of descriptions of the phenomena with which the theory deals. A theory is associated with a methodology used to obtain the descriptions. Implementations are computer systems that use the descriptions to solve specific problems in text processing. Implementations of ontological semantics are combined with other processing systems to produce applications, such as information extraction or machine translation. The theory of ontological semantics is built as a society of microtheories covering such diverse ground as specific language phenomena, world knowledge organization, processing heuristics and issues relating to knowledge representation and implementation system architecture. The theory briefly sketched above is a top-level microtheory, the ontological semantics theory per se. Descriptions in ontological semantics include text meaning representations, lexical entries, ontological concepts and instances as well as procedures for manipulating texts and their meanings. Methodologies in ontological semantics are sets of techniques and instructions for acquiring and

is it unique to humans?