All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the…

In this paper we explore the degree to which patents are representative of the magnitude,
direction, and impact of the knowledge spilling out of the university by focusing on MIT, and in particular on the departments of Mechanical and Electrical…

The goal of the work reported here is to capture the commonsense knowledge of non-expert human contributors. Achieving this goal will enable more intelligent human-computer interfaces and pave the way for computers to reason about our world. In the domain…

In recent years, researchers in artificial intelligence have become interested in replicating human physical reasoning talents in computers. One of the most important skills in this area is predicting how physical systems will behave. This thesis discusses an implemented program…

This paper describes a system for the computer understanding of English. The system answers questions, executes commands, and accepts information in normal English dialog. It uses semantic information and context to understand discourse and to disambiguate sentences. It combines a…

Data quality issues have taken on increasing importance in recent years. In our research, we have discovered that many “data quality” problems are actually “data misinterpretation” problems – that is, problems with data semantics. In this paper, we first illustrate…

This paper presents an adaptive learning model for market-making under the reinforcement learning framework. Reinforcement learning is a learning technique in which agents aim to maximize the long-term accumulated rewards. No knowledge of the market environment, such as the order…

This paper presents an intelligent, hybrid system for stamping process planning in progressive die design. The system combines the flexibility of blackboard architecture with case-based reasoning. The hybrid system has the advantage that it can use past knowledge and experience…

The purpose of this paper is to introduce patent litigation as a leading indicator of market
growth. We model the intensity of patent litigation and the market growth for the
personal computer and cellular phone market in the US. By…

This thesis considers three complications that arise from applying reinforcement learning to a real-world application. In the process of using reinforcement learning to build an adaptive electronic market-maker, we find the sparsity of data, the partial observability of the domain,…