Empirically successful computerized reasoning

LPAR-05 Workshop: Empirically Successful Automated Reasoning in Higher-Order Logic (ESHOL)

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Why Is Linear Quantile Regression Empirically Successful: A Possible Explanation

Many quantities describing the physical world are related to each other. As a result, often, when we know the values of certain quantities x1, . . . , xn, we can reasonably well predict the value of some other quantity y. In many application, in addition to the resulting estimate for y, it is also desirable to predict how accurate is this approximate estimate, i.e., what is the probability dist...

Using Four Values for Computerized Reasoning

Modeling recursive reasoning by humans using empirically informed interactive POMDPs

Recursive reasoning of the form what do I think that you think that I think (and so on) arises often while acting rationally in multiagent settings. Several multiagent decision-making frameworks such as RMM, I-POMDP and the theory of mind model recursive reasoning as integral to an agent’s rational choice. Real-world application settings for multiagent decision making are often mixed involving ...

FRACAS: A Computerized Aid for Reasoning in Tax

Problem solving in the tax domain requires two kinds of knowledge: of the law itself and of how the law has been applied in the past. The need for the second factor arises as a result of the ambiguity of natural language. The problem solver requires information on how the courts have adjudicated specific cases in the past. This information would then provide the basis for reasoning about the cu...