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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 2 of 2 (0.027 seconds)| 1 |
A belief-desire-intention architechture with a logic-based planner for agents in stochastic domainsRens, Gavin B. 02 1900 (has links)
This dissertation investigates high-level decision making for agents that are both goal and utility
driven. We develop a partially observable Markov decision process (POMDP) planner which
is an extension of an agent programming language called DTGolog, itself an extension of the
Golog language. Golog is based on a logic for reasoning about action—the situation calculus.
A POMDP planner on its own cannot cope well with dynamically changing environments
and complicated goals. This is exactly a strength of the belief-desire-intention (BDI) model:
BDI theory has been developed to design agents that can select goals intelligently, dynamically
abandon and adopt new goals, and yet commit to intentions for achieving goals. The contribution
of this research is twofold: (1) developing a relational POMDP planner for cognitive
robotics, (2) specifying a preliminary BDI architecture that can deal with stochasticity in action
and perception, by employing the planner. / Computing / M. Sc. (Computer Science)
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A belief-desire-intention architechture with a logic-based planner for agents in stochastic domainsRens, Gavin B. 02 1900 (has links)
This dissertation investigates high-level decision making for agents that are both goal and utility
driven. We develop a partially observable Markov decision process (POMDP) planner which
is an extension of an agent programming language called DTGolog, itself an extension of the
Golog language. Golog is based on a logic for reasoning about action—the situation calculus.
A POMDP planner on its own cannot cope well with dynamically changing environments
and complicated goals. This is exactly a strength of the belief-desire-intention (BDI) model:
BDI theory has been developed to design agents that can select goals intelligently, dynamically
abandon and adopt new goals, and yet commit to intentions for achieving goals. The contribution
of this research is twofold: (1) developing a relational POMDP planner for cognitive
robotics, (2) specifying a preliminary BDI architecture that can deal with stochasticity in action
and perception, by employing the planner. / Computing / M. Sc. (Computer Science)
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