A new inductive learning system, Lab Learning for ABduction, is presented which acquires abductive rules from a set of training examples. The goal is to nd a small knowledge base ...
We present new algorithms for local planning over Markov decision processes. The base-level algorithm possesses several interesting features for control of computation, based on s...
The goals of situated agents generally do not specify particular objects: they require only that some suitable object should be chosen and manipulated (e.g. any red block). Situat...
1 We have developed an approach to acquire complicated user optimization criteria and use them to guide iterative solution improvement. The eectiveness of the approach was tested ...
This paper proposes a method to find the most suitable architecture for a given response time requirement for Example-Retrieval (ER), which searches for the best match from a bulk...
In this paper we present a model for coalition formation and payo distribution in general environments. We focus on a reduced complexity kernel-oriented coalition formation model,...
Arc consistency filtering is widely used in the framework of binary constraint satisfaction problems: with a low complexity, inconsistency may be detected,and domains are filtered...
We present a formal theory of model-based testing, an algorithm for test generation based on it, and outline how testing is implemented by a diagnostic engine. The key to making t...
Theperformanceof individual agents in a group dependscritically on the quality of information available to it about local and global goals and resources. In general it is assumed ...