Implementing Lexical And Creative Intentionality In Synthetic Personality

Creating engaging, interactive, and immersive synthetic characters is a difficult task and evaluating the success of a synthetic character is often even more difficult. The later problem is solved by extending Turing\u27s Imitation Game thusly: computational construct should be evaluated based on the criteria of how well the character can mimic a human. In order to accomplish a successful evaluation of the proposed metric, synthetic characters must be consistently believable and capable of role-appropriate emotional expression. The author believes traditional synthetic characters must be improved to meet this goal. For a synthetic character to be believable, human users must be able to perceive a link between the mental state of the character and its behaviors. That is to say, synthetic characters must possess intentionality. In addition to intentionality, the mental state of the character must be human-like in order to provide an adequate frame of reference for the human users\u27 internal simulations, to wit, the character\u27s mental state must be comprised of a synthetic model of personality, of personality dynamics, and of cognition, each of which must be psychologically valid and of sufficient fidelity for the type of character represented. The author proposes that synthetic characters possessing these three models are more accurately described as synthetic personalities. The author proposes and implements computational models of personality, personality dynamics, and cognition in order to evaluate the psychological veracity of these models and computational equivalence between the models and the implementation as a first step in the process of creating believable synthetic personalities

Synthetic social relationships for computational entities

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2002.Includes bibliographical references (p. 179-189).Humans and many other animals form long term social relationships with each other. These relationships confer a variety of benefits upon us, both as individuals and as groups. Computational systems that can form social relationships like those formed by animals could reap many of the benefits of sociality, both within their own groups and in their interactions with people. This dissertation explores two main questions: *What kinds of internal and external representations are necessary for computational entities to form social relationships like those formed by animals? *How can people participate in and direct the relationships of these entities? To explore these questions, I designed and implemented a system by which computational entities may form simple social relationships. In particular, these synthetic social relationships are modeled after the social behavior of the gray wolf (Canis lupus). The system comprises a novel combination of simple models of emotion, perception and learning in an emotional memory-based mechanism for social relationship formation. The system also includes supporting technologies through which people may participate in and direct the relationships. The system was presented as an interactive installation entitled AlphaWolf in the Emerging Technologies program at SIGGRAPH 2001. This installation featured a pack of six virtual wolves - three fully autonomous adults and three semi-autonomous pups whom people could direct by howling, growling, whining or barking into microphones.(cont.) In addition to observing the interactions of several hundred SIGGRAPH participants, I performed two main evaluations of the AlphaWolf system - a 32-subject human user study and a set of simulations of resource exploitation among the virtual wolves. Results from these evaluations support the hypothesis that the AlphaWolf system enables the formation of social relationships among groups of computational entities and people, and that these relationships are beneficial to both the inter-machine interactions and the human-machine interactions in a variety of ways. This research represents one of many possible steps towards synthetic social relationships with the complexity of the relationships found in real wolves, let alone in humans. Much further work will be necessary to create entities who can fully engage us in our own social terms. The system presented here provides a basic scaffolding on which such entities may be built, including an implemented, real-time example; new ideas in directable characters and character-based interactive installations; a simple, ethologically plausible model of computational social relationships; and statistically significant support for these claims.by William Michael Tomlinson, Jr.Ph.D

A Logical Approach to High-Level Agent Control

The Publisher's final version can be found by following the DOI linkRecent work in animated human-like agent has made impressive progress toward generating agents with believable appearances and realistic motions for the interactive applications of inhabited virtual worlds. It remains difficult, however, to instruct animated agents to perform specific tasks or take initiatives. This paper addresses the challenge of instructability by introducing cognitive modelling - a novel logical approach based on a highly developed logical theory of actions, i. e. Event Calculus. Cognitive models go beyond behavioural models in that they govern an agent's behaviour by reasoning about its knowledge, actions and events. To facilitate the construction of the language (BSL) from the event calculus formalism. Using BSL, we can specify and agent's domain knowledge, design behaviour controllers and then control the agent's behaviour in terms of goals and/ or goals and/ or user's instructions. This approach allows agent's behaviours to be specified and controlled more naturally and intuitively, more succinctly and at a much highter level of abstraction than would otherwise be possible. It als provides a logical characterisation of planning via abductive reasoning process. Furthermore, we integrate sensing capability into our underlying theoretical framework, thus enabling animated agents to generate appropriate behaviour even in complex, dynamic virtual worlds. An animated human- like interface agent for virtual environments is used to demonstrate the approach. The architecture for implementing the approach is also described