talk: Human-Like Strategies for Language-Endowed Intelligent Agents, 11am Fri 4/48, UMBC

Mon, 24 Apr 2017 00:24:52 -0400
ai, computer-science, news, talks

The UMBC Center for Hybrid Multicore Productivity Research (CHMPR)
is pleased to present as part of our distinguished lecture series

Human-Like Strategies for Language-Endowed Intelligent Agents

Dr. Sergei Nirenburg
Professor of Cognitive Science
Rensselaer Polytechnic Institute

11:00am Friday, 28 April 2017, ITE 325b

Artificial intelligent agents functioning in human-agent teams must correctly interpret perceptual input and make appropriate decisions about their actions. These are arguably the two central problems in computational cognitive modeling. The RPI LEIA Lab builds language-endowed intelligent agents that extract meaning of text and dialog and use the results together with input from other perception modes, a long-term belief repository, rich models of the world and of other agents, and a model of the interaction situation to make decisions about actions. Specific phenomena we currently concentrate on include incrementality, treatment of unexpected input and non-literal language (e.g., metaphor), analysis of agent biases and “mindreading,” and deliberate concept learning. All these studies are characterized by our belief in the ultimate utility of building causal models of agent capabilities that are inspired by human strategies in language processing and decision-making that go beyond analogical reasoning. In this talk I will give an overview of our recent work in the above areas.

Sergei Nirenburg is Professor of Cognitive Science and Computer Science at the Rensselaer Polytechnic Institute. He also serves as Head of the Department of Cognitive Science. He has worked in the areas of cognitive science, artificial intelligence and natural language processing for over 35 years, leading R&D teams of up to 80. Dr. Nirenburg’s professional interests include developing computational models of human cognitive capabilities and implementing them in computer models of societies of human and computer agents, continuing development of the theory of ontological semantics, and the acquisition and management of knowledge about the world and about language. Academic R&D teams under Dr. Nirenburg’s leadership have implemented a variety of proof-of-concept and prototype application systems for cognitive modeling, intelligent tutoring and a variety of NLP tasks (machine translation, question answering, text summarization, information extraction, computational field linguistics, knowledge elicitation and learning). Dr. Nirenburg has written two and edited five books and published over 200 scholarly articles in journals and peer-reviewed conference proceedings.