We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
There have been many proposals to compute similarities between words based on their distributions in contexts. However, these approaches do not distinguish between synonyms and an...
This paper addresses agents' intentions as building blocks of imitation learning that abstract local situations of the agent, and proposes a hierarchical hidden Markov model ...
We propose a novel method for constructing utility models by learning from observed negotiation actions. In particular, we show how offers and counter-offers in negotiation can be...
In this paper we present the monotonicity principle, a sufficient condition to ensure that exact mapping, a mapping as would be performed by a human observer, is ranked close to ...
Ateret Anaby-Tavor, Avigdor Gal, Alberto Trombetta