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MBP: a Model Based Planner

MBP: a Model Based Planner. The NuPDDL input language. The Model Based Planner (MBP) is a system designed to perform plan synthesis, plan validation and plan/domain simulation in non-deterministic domains. It provides:. A general framework for modeling nondeterministic domains with various degrees of observability, and a language. A general plan model, and a language. Supporting it with powerful primitives. Capabilities, expressing plan validation as a model checking problem. A means for simulation.

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MBP: a Model Based Planner | mbp.fbk.eu Reviews

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MBP: a Model Based Planner. The NuPDDL input language. The Model Based Planner (MBP) is a system designed to perform plan synthesis, plan validation and plan/domain simulation in non-deterministic domains. It provides:. A general framework for modeling nondeterministic domains with various degrees of observability, and a language. A general plan model, and a language. Supporting it with powerful primitives. Capabilities, expressing plan validation as a model checking problem. A means for simulation.

<META> KEYWORDS

1 overview

2 plan synthesis

3 plan validation

4 synthesis of controllers

5 plan/domain simulation

6 download

7 related planners

8 to support it

9 to the assignments

10 conformant planning

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overview,plan synthesis,plan validation,synthesis of controllers,plan/domain simulation,download,related planners,to support it,to the assignments,conformant planning,mbp validate nupddl files,where,nupddl files,plan/ domain simulation,language,in nupddl

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MBP: a Model Based Planner | mbp.fbk.eu Reviews

https://mbp.fbk.eu

MBP: a Model Based Planner. The NuPDDL input language. The Model Based Planner (MBP) is a system designed to perform plan synthesis, plan validation and plan/domain simulation in non-deterministic domains. It provides:. A general framework for modeling nondeterministic domains with various degrees of observability, and a language. A general plan model, and a language. Supporting it with powerful primitives. Capabilities, expressing plan validation as a model checking problem. A means for simulation.

INTERNAL PAGES

mbp.fbk.eu

1

NuPDDL: MBP's input language

http://mbp.fbk.eu/NuPDDL.html

NuPDDL: nondeterminism and more in PDDL. Modeling of uncertainty in initial states. And nondeterminstic action effects. Modeling of partial observability. Modeling of a variety of problem classes. Embeds a powerful, general plan language. NuPDDL retains most of PDDL2.1, including the handling of functions, conditional effects, and quantifiers. In NuPDDL, arbitrary nesting of conditional effects and/or quantifiers is legal. In the current NuPDDL version, the following restrictions apply:. The keywords one...

2

Synthesis of controllers with MBP

http://mbp.fbk.eu/scmbp.html

Synthesis of controllers with MBP. MBP tool along with plan synthesis. Allows to synthesize (maximally permissive) controllers. It takes as the input a plant (or domain; a state-transition system) written in SMV language. And requirements as CTL formulae. Also, MBP allows one to simulate behaviours of both the uncontrolled plant (domain) and the controlled one. Finally, it benefits from the common language with NuSMV Symbolic Model Checker. To synthesize the controller, run. MBP -dsimulate smv file.

3

- AIPS'02 Tutorial -Planning as Model Checking

http://mbp.fbk.eu/AIPS02-tutorial.html

Planning as Model Checking. Via Sommarive 18, 39055 Povo (TN) - Italy. Bertoli,pistore,roveri}@fbk.eu. This tutorial is sponsored by PLANET. The European Network of Excellence in AI Planning. This tutorial will be held at AIPS'02. On April, 24. Please look at this page. For further information on the AIPS'02 tutorials. In the last few years, Model Checking has been shown to be a very effective approach to Planning. In Model Checking [ 6. Several planning systems are based on different kinds of Model Chec...

4

Planning for Partially Observable domains

http://mbp.fbk.eu/po.html

Planning under Partial Observability. In the general case, only part of the information on the status of a (possibly nondeterministic) domain is available at run-time (e.g. via sensors). MBP allows the user to model "partially observable" domains, stating what is observable of their status, and to build strong plans for problems of reachability in these domains. "Faulty" sensing can also be modeled in MBP. Further information on planning under partial observability can be found here. L12 l56 - line).

5

Conformant Planning

http://mbp.fbk.eu/conformant.html

Conformant planning means "synthesizing a strong plan under the assumption of null run-time observability". A conformant plan consists of a sequence of actions that is guaranteed to achieve the goal regardless of the uncertainty in the initial condition and in the nondeterministic effects of actions. Further information on conformant planning can be found here. Consider the example depicted below. A stack of five numbers must be sorted in ascendent order. A " binary sort". Define (domain conformant sort).

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nusmv.fbk.eu

NuSMV home page

http://nusmv.fbk.eu/index.html

NuSMV: a new symbolic model checker. NuSMV 2.6.0 is OUT! NuXmv 1.0.0. A new symbolic model checker for the analysis of synchronous finite-state and infinite-state systems is OUT. NuSMV 2.6.0 is a major release that comes after four years passed working under the surface. The release provides some new features, many bug fixes and optimizations, and substantial differences in the software architecture and building system. To retrieve a copy. Read the announce for NuSMV 2.6.0. Read the announce for NuSMV 2.

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