In this paper we propose a new approach to planning based on a `high level action language`, called AR, and `model checking`. AR is an expressive formalism which is able to handle, among other things, ramifications and non-deterministic effects. We define a decision procedure for planning in AR which is based on `symbolic model checking`, a technique which has been sucessfully applied in hardware and software verification. The decision procedure always terminates with an optimal solution or with failure if no solution exists. We have constructed a planner, called MBP, which implements the decision procedur
textEffective plan specification, solution extraction and plan execution are critical to the abilit...
We describe a planning algorithm that integrates two approaches to solving Markov decision processe...
MIPS, model checking has eventually approached classical AI planning. It was the first planning syst...
In the thesis is tackled the Artificial Intelligence (AI) problem of Automatic Planning using Symbol...
The Model Based Planner (MBP) is a system for planning in non-deterministic domains. It can generate...
Planning via Model Checking is a novel approach to planning. It is based on the reformulation of a p...
We tackle the problem of planning in nondeterministic domains, by presenting a new approach to confo...
We tackle the problem of planning in nondeterministic domains, by presenting a new approach to confo...
Conformant planning is the problem of finding a sequence of actions that is guaranteed to achieve th...
Interleaving planning and execution is the practical alternative to the problem of planning off-line...
The Model Based Planner (MBP) is a system for planning in non-deterministic domains. It can generate...
Planning via Model Checking is nowadays a well-known technique. Techniques based on model checking h...
Formal verification of hardware and software systems in-volves proving or disproving the correctness...
The past few years have seen a flurry of new approaches for planning under uncertainty, but their ap...
Planning in nondeterministic domains yields both conceptual and practical difficulties. From the con...
textEffective plan specification, solution extraction and plan execution are critical to the abilit...
We describe a planning algorithm that integrates two approaches to solving Markov decision processe...
MIPS, model checking has eventually approached classical AI planning. It was the first planning syst...
In the thesis is tackled the Artificial Intelligence (AI) problem of Automatic Planning using Symbol...
The Model Based Planner (MBP) is a system for planning in non-deterministic domains. It can generate...
Planning via Model Checking is a novel approach to planning. It is based on the reformulation of a p...
We tackle the problem of planning in nondeterministic domains, by presenting a new approach to confo...
We tackle the problem of planning in nondeterministic domains, by presenting a new approach to confo...
Conformant planning is the problem of finding a sequence of actions that is guaranteed to achieve th...
Interleaving planning and execution is the practical alternative to the problem of planning off-line...
The Model Based Planner (MBP) is a system for planning in non-deterministic domains. It can generate...
Planning via Model Checking is nowadays a well-known technique. Techniques based on model checking h...
Formal verification of hardware and software systems in-volves proving or disproving the correctness...
The past few years have seen a flurry of new approaches for planning under uncertainty, but their ap...
Planning in nondeterministic domains yields both conceptual and practical difficulties. From the con...
textEffective plan specification, solution extraction and plan execution are critical to the abilit...
We describe a planning algorithm that integrates two approaches to solving Markov decision processe...
MIPS, model checking has eventually approached classical AI planning. It was the first planning syst...