Sciweavers

AAAI
1998
13 years 11 months ago
Iterated Phantom Induction: A Little Knowledge Can Go a Long Way
Weadvance a knowledge-based learning method that augments conventional generalization to permit concept acquisition in failure domains. These are domains in whichlearning must pro...
Mark Brodie, Gerald DeJong
AAAI
1998
13 years 11 months ago
A Motivational System for Regulating Human-Robot Interaction
This paper presents a motivational system for an autonomous robot which is designed to regulate human-robot interaction. The mode of social interaction is that of a caretaker-infa...
Cynthia Breazeal
AAAI
2000
13 years 11 months ago
From Causal Theories to Successor State Axioms and STRIPS-Like Systems
We describe a system for specifying the effects of actions. Unlike those commonly used in AI planning, our system uses an action description language that allows one to specify th...
Fangzhen Lin
AAAI
1998
13 years 11 months ago
Generalizing Partial Order and Dynamic Backtracking
RecentlyFtwo new backtracking algorithmsF dynamic backtracking (DB)and partial order dynamicbacktracking (PDB) have been presented. These algorithms have the property to be additi...
Christian Bliek
AAAI
2000
13 years 11 months ago
Decision-Theoretic, High-Level Agent Programming in the Situation Calculus
We propose a frameworkfor robot programming which allows the seamless integration of explicit agent programming with decision-theoretic planning. Specifically, the DTGolog model a...
Craig Boutilier, Raymond Reiter, Mikhail Soutchans...
AAAI
1998
13 years 11 months ago
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
This paper describes STAGE, a learning approach to automatically improving search performance on optimization problems.STAGElearns an evaluation function which predicts the outcom...
Justin A. Boyan, Andrew W. Moore
AAAI
1998
13 years 11 months ago
Belief Revision with Unreliable Observations
Research in belief revision has been dominated by work that lies firmly within the classic AGM paradigm, characterized by a well-known set of postulates governing the behavior of ...
Craig Boutilier, Nir Friedman, Joseph Y. Halpern
AAAI
2000
13 years 11 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
AAAI
1998
13 years 11 months ago
Opponent Modeling in Poker
Poker is an interesting test-bed for artificial intelligence research. It is a game of imperfect knowledge, where multiple competing agents must deal with risk management, agent m...
Darse Billings, Denis Papp, Jonathan Schaeffer, Du...