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MODELING SOCIAL CAUSALITY AND SOCIAL JUDGMENT IN
MULTI-AGENT INTERACTIONS
by
Wenji Mao
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
December 2006
Copyright 2006 Wenji Mao
Object Description
| Title | Modeling social causality and social judgment in multi-agent interactions |
| Author | Mao, Wenji |
| Author email | wenjimao@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2006-07-24 |
| Date submitted | 2006 |
| Restricted until | Unrestricted |
| Date published | 2006-09-29 |
| Advisor (committee chair) | Gratch, Jonathan |
| Advisor (committee member) |
Rosenbloom, Paul Read, Stephen J. |
| Abstract | Intelligent Agents are typically situated in a social environment and must reason about social cause and effect. Social causal reasoning is qualitatively different from physical causal reasoning that underlies most intelligent systems. Modeling the process and inference of social causality can enrich the capabilities of multi-agent and intelligent interactive systems. In this thesis, first we explore the underlying theory and process of how people evaluate social events, and present a domain-independent computational framework to reason about social cause and responsibility. The computational framework can be generally incorporated into an intelligent system to augment its cognitive and social functionality.; For the fidelity of the modeling, this work is based on psychological attribution theory. Attribution theory identifies several key factors people use in forming their judgments, such as physical cause, intentions, foreknowledge and coercion. Based on the theory, our work formalizes commonsense reasoning of deriving the beliefs about the key factors from natural language communication and task execution. In addition to developing the model, we design and conduct experiments to empirically validate the model, using real human data. The experimental results show that model predictions of the overall judgments, intermediate beliefs about the variables and inferential mechanism are consistent with people responses.; The computational framework has been applied to several applications, such as emotion modeling, natural language conversation strategies and performance assessment in group training. Other potential applications include interactive system design, adaptive user interfaces and coherent internal models for virtual humans. In the end of the dissertation, we summarize the research contributions and raise some issues for future considerations. |
| Keyword | intelligent agents; cognitive modeling; social inference; causality; commonsense reasoning |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m55 |
| Rights | Mao, Wenji |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Mao-20060929 |
| Archival file | uscthesesreloadpub_Volume4/etd-Mao-20060929.pdf |
Description
| Title | Page 1 |
| Full text | MODELING SOCIAL CAUSALITY AND SOCIAL JUDGMENT IN MULTI-AGENT INTERACTIONS by Wenji Mao A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COMPUTER SCIENCE) December 2006 Copyright 2006 Wenji Mao |
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