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Found 5 papers, 0 papers with code
A Linear Programming Approach for Resource-Aware Information-Theoretic Tree Abstractions
It is shown that the resulting information-theoretic abstraction problem over the space of multi-resolution trees can be formulated as a integer linear programming (ILP) problem.
Information-Theoretic Abstractions for Resource-Constrained Agents via Mixed-Integer Linear Programming
In this paper, a mixed-integer linear programming formulation for the problem of obtaining task-relevant, multi-resolution, graph abstractions for resource-constrained agents is presented.
Information-Theoretic Abstractions for Planning in Agents with Computational Constraints
In this paper, we develop a framework for path-planning on abstractions that are not provided to the agent a priori but instead emerge as a function of the available computational resources.
Q-Search Trees: An Information-Theoretic Approach Towards Hierarchical Abstractions for Agents with Computational Limitations
In this paper, we develop a framework to obtain graph abstractions for decision-making by an agent where the abstractions emerge as a function of the agent's limited computational resources.
Hierarchical State Abstractions for Decision-Making Problems with Computational Constraints
In this semi-tutorial paper, we first review the information-theoretic approach to account for the computational costs incurred during the search for optimal actions in a sequential decision-making problem.
