Towards Action Prediction Using a Mental-Level Model
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Temporal Reasoning. Pages 2010-2015.
Abstract
We propose a formal approach to the problem of prediction based on the following steps: First, a mental-level model is constructed based on the agent's previous actions; next, the model is updated to account for any new observations by the agent, and finally, we predict the optimal action w.r.t . the agent's mental state as its next action. This paper formalizes this prediction process. In order to carry out this process, we need to understand how a mental state can be ascribed to an agent and how this mental state should be updated. In [Brafman and Tennenholtz, 1994b], we examined the first stage. Here we investigate a particular update operator and show that its ascription requires making only weak modeling assumptions.
@inproceedings{ijcai1995p258,
title = {Towards Action Prediction Using a Mental-Level Model},
author = {Brafman, Ronen I. and Tennenholtz, Moshe},
booktitle = {Proceedings of the Fourteenth International Joint Conference on
Artificial Intelligence, {IJCAI-95}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Chris S. Mellish},
pages = {2010--2015},
year = {1995},
note = {Temporal Reasoning},
url = {https://ijcai.org/proceedings/1995/258},
}
TY - CPAPER TI - Towards Action Prediction Using a Mental-Level Model AU - Brafman, Ronen I. AU - Tennenholtz, Moshe T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 2010 EP - 2015 UR - https://ijcai.org/proceedings/1995/258 ER -Copied
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