Compelling synthetic characters must behave in ways that reflect their past experience and thus allow for individual personalization. We therefore need a method that allows charac...
Song-Yee Yoon, Robert C. Burke, Bruce Blumberg, Ge...
This paper presents a new combinatorial auction protocol (LDS protocol) that is robust against false-name bids. Internet auctions have become an integral part of Electronic Commer...
Depth-first branch-and-bound (DFBnB) is a complete algorithm that is typically used to find optimal solutions of difficult combinatorial optimization problems. It can also be adap...
Finding information is a problem shared by people and intelligent systems. This paper describes an experiment combining both human and machine aspects in a knowledgebased system t...
Our work is driven by one of the core purposes of artificial intelligence: to develop real robotic agents that achieve complex high-level goals in real-time environments. Robotic ...
We describe MarketSAT, a highly decentralized, marketbased algorithm for propositional satisfiability. The approach is based on a formulation of satisfiability as production on a ...
The ontology used by most card catalog and bibliographic systems is based on a now outdated assumption that users of the systems would be looking for books on shelves, and therefo...
Systems that learn from examples often express the learned concept in the form of a disjunctive description. Disjuncts that correctly classify few training examples are known as s...
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...