We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
A recurring theme in AI and multiagent systems is how to select the "most desirable" elements given a binary dominance relation on a set of alternatives. Schwartz's...
Felix Brandt, Felix A. Fischer, Paul Harrenstein, ...
When autonomous agents decide on their bidding strategies in real world auctions, they have a number of concerns that go beyond the models that are normally analyzed in traditiona...
In this paper, a state-based approach for the Constraint Satisfaction Problem (CSP) is proposed. The key novelty is an original use of state memorization during search to prevent ...
This paper investigates hindsight optimization as an approach for leveraging the significant advances in deterministic planning for action selection in probabilistic domains. Hind...
Sung Wook Yoon, Alan Fern, Robert Givan, Subbarao ...