JAIR
2011
12 years 11 months ago
2011
Bound propagation is an important Artificial Intelligence technique used in Constraint Programming tools to deal with numerical constraints. It is typically embedded within a sea...
JAIR
2011
12 years 11 months ago
2011
Temporal information has been the focus of recent attention in information extraction, leading to some standardization effort, in particular for the task of relating events in a t...
JAIR
2011
12 years 11 months ago
2011
We define a logic of propositional formula schemata adding to the syntax of propositional logic indexed propositions (e.g., pi) and iterated connectives ∨ or ∧ ranging over i...
JAIR
2011
12 years 11 months ago
2011
Leading agent-based trust models address two important needs. First, they show how an agent may estimate the trustworthiness of another agent based on prior interactions. Second, ...
JAIR
2011
12 years 11 months ago
2011
We introduce a novel logical notion–partial entailment–to propositional logic. In contrast with classical entailment, that a formula P partially entails another formula Q with...
JAIR
2011
12 years 11 months ago
2011
In this paper, we propose a comprehensive study of second-order consistencies (i.e., consistencies identifying inconsistent pairs of values) for constraint satisfaction. We build ...
JAIR
2011
12 years 11 months ago
2011
In action domains where agents may have erroneous beliefs, reasoning about the effects of actions involves reasoning about belief change. In this paper, we use a transition system...
JAIR
2011
12 years 11 months ago
2011
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
JAIR
2011
12 years 11 months ago
2011
We present a method for using standard techniques from satisfiability checking to automatically verify and discover theorems in an area of economic theory known as ranking sets o...
JAIR
2011
12 years 11 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...