In this article we work on certain aspects of the belief change theory in order to make them suitable for argumentation systems. This approach is based on Defeasible Logic Program...
Machine learning approaches to indoor WiFi localization involve an offline phase and an online phase. In the offline phase, data are collected from an environment to build a local...
Sinno Jialin Pan, Dou Shen, Qiang Yang, James T. K...
Horn-to-Horn belief revision asks for the revision of a Horn knowledge base such that the revised knowledge base is also Horn. Horn knowledge bases are important whenever one is c...
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
In group decision making, often the agents need to decide on multiple attributes at the same time, so that there are exponentially many alternatives. In this case, it is unrealist...
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...
We consider a multiagent extension of single-agent graph coloring. Multiple agents hold disjoint autonomous subgraphs of a global graph, and every color used by the agents in colo...
When autonomous agents decide on their bidding strategies in real world auctions, they have a number of concerns that go beyond the models that are normally analyzed in traditiona...