Two standard schemes for learning in classifier systems have been proposed in the literature: the bucket brigade algorithm (BBA) and the profit sharing plan (PSP). The BBA is a lo...
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Bounded response time is an important requirement when rule-based expert systems are used in real-time applications. In the case the rule-based system cannot terminate in bounded ...
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...
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...
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...
This paper describes experiments documenting significant variations in word usage patterns within social subgroups of AI researchers. As some phrases have very different collocati...
This research explores the interaction of textual and photographic information in document understanding. The problem of performing generalpurpose vision without apriori knowledge...