We analyze the complexity of propositional kernel resolution (del Val 1999), a general method for obtaining logical consequences in restricted target languages. Different choices ...
This paper presents a new vision-based obstacle detection method for mobile robots. Each individual image pixel is classified as belonging either to an obstacle or the ground base...
We consider the use of multi-agent systems to control network routing. Conventional approaches to this task are based on Ideal Shortest Path routing Algorithm (ISPA), under which ...
The main problem of planning is to find a sequence of actions that an agent must perform to achieve a given objective. An important part of planning is checking whether a given pl...
Gridworlds are popular testbeds for planning with incomplete information but not much is known about their properties. We study a fundamental planning problem, localization, to in...
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
Monte Carlo localization (MCL) is a Bayesian algorithm for mobile robot localization based on particle filters, which has enjoyed great practical success. This paper points out a ...
We present a new domain for unsupervised learning: automatically customizing the computer to a specific melodic performer by merely listening to them improvise. We also describe B...