Charles Ortiz

Charles Ortiz
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Main area of research
Natural language & AI

Charles Ortiz is the Senior Principal Manager of the Artificial Intelligence and Reasoning Group at the Nuance Natural Language and AI Laboratory in Sunnyvale California.  His research at Nuance focuses on collaborative dialog systems and commonsense reasoning for personal assistants. Prior to joining Nuance, he was the director of research in collaborative multi-agent systems at the AI Center at SRI International. His research interests and contributions are in multiagent systems (collaborative dialogue-structured assistants, collaborative work environments, negotiation protocols, and logic-based BDI theories), knowledge representation and reasoning (causation, counterfactuals, and commonsense reasoning), and robotics (cognitive robotics, team-based robotics, and dialogue-based human-robot interaction). He has approximately 20 years of technical leadership and management experience in leading major projects and setting strategic directions. He has collaborated extensively with faculty and students at many academic institutions including Harvard University, Bar-Ilan University, UC Berkeley, Columbia University, University of Southern California, Vassar College, and Carnegie Mellon University. He holds an S.B. in Physics from MIT, an M.S. in Computer Science from Columbia University, and a Ph.D. in Computer and Information Science from the University of Pennsylvania. Following his PhD research, he was a Postdoctoral Research Fellow at Harvard University. He has taught courses at Harvard and was also an adjunct faculty member at UC Berkeley.  He has presented numerous tutorials at technical conferences (IJCAI 1999 and 2005, AAAI 2002 and 2004, AAMAS 2002-2004).

Selected articles

Hierarchical information combination process for large-scale task and team environments

 In this paper, we describe the Distributed Dispatcher Manager (DDM), a system for monitoring large collections of dynamically changing tasks. We assume that tasks are

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Interpreting information requests in context: a collaborative web interface for distance learning

We describe the use of theories of agent collaboration and human dialogue processing in providing a principled basis for the design of web interfaces to

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Hierarchical organizations for real-time large-scale task and team environments

In this paper, we describe the Distributed Dispatcher Manager (DDM), a system for monitoring large collections of dynamically changing tasks. We assume that tasks are

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Structured negotiation

Structured negotiation is proposed as a new method through which collaborating agents can seek consensus on the apportionment of tasks and resources. The approach draws

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Multilevel adaptation in teams of unmanned air and ground vehicles

We describe ongoing work to develop algorithms and software for the reprogrammable, coordinated command and control of teams of autonomous vehicles (AVs). This new software

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