A model for reasoning about persistence and causation
Computational Intelligence
Planning and acting in partially observable stochastic domains
Artificial Intelligence
Conversation as Action Under Uncertainty
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Persistence matters: making the most of chat in tightly-coupled work
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Action as language in a shared visual space
CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
Visual information as a conversational resource in collaborative physical tasks
Human-Computer Interaction
Degrees of grounding based on evidence of understanding
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
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A Situated Conversational Agent (SCA) is an agent that engages in dialog about the context within which it is embedded. An SCA is distinguished from non-situated conversational agents by an intimate connection of the agent's dialog to its embedding context, and by intricate dependencies between its linguistic and physical actions. Constructing an SCA that can interact naturally with users while engaged in collaborative physical tasks requires the agent to interleave decision making under uncertainty, action execution, and observation while maximizing expected utility over a sequence of interactions. These requirements can be fulfilled by modeling an SCA as a partially observable Markov decision process (POMDP). We show how POMDPs can be used to formalize and implement psycholinguistic proposals on how situated dialog participants collaborate in order to make and ground dialog contributions.