Applications of a theory of automated adversarial planning to command and control
IEEE Transactions on Systems, Man and Cybernetics
Multipurpose adversary planning in the game of go
Multipurpose adversary planning in the game of go
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
The structure and performance of the interim.2 go program
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
A chronology of computer chess and its literature
Artificial Intelligence
Total-order multi-agent task-network planning for contract bridge
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
Adversarial behavior in multi-agent systems
CEEMAS'05 Proceedings of the 4th international Central and Eastern European conference on Multi-Agent Systems and Applications
The adversarial activity model for bounded rational agents
Autonomous Agents and Multi-Agent Systems
Searching for compound goals using relevancy zones in the game of go
CG'04 Proceedings of the 4th international conference on Computers and Games
| Hi-index | 0.00 |
Approaches to computer game playing based on (typically α-β) search of the tree of possible move sequences combined with an evaluation function have been successful for many games, notably Chess. For games with large search spaces and complex positions, such as Go, these approaches are less successful and we are led to seek alternative approaches. One such alternative is to model the goals of the players, and their strategies for achieving these goals. This approach means searching the space of possible goal expansions, typically much smaller than the space of move sequences. In this paper we describe how adversarial hierarchical task network planning can provide a framework for goal-directed game playing, and its application to the game of Go.