Planeamento

 

Respons·vel: AmÌlcar Cardoso

Programa

  1. Bibliografia
  2. IntroduÁ“o
  3. Planeamento como Procura num EspaÁo de Estados
  4. C·lculo Situacional
  5. Sistema STRIPS
  6. Planeamento por Ordem Parcial

Bibliografia

Stuart RUSSEL e Peter NORVIG, Artificial Intelligence: a Modern Approach, Prentice Hall, 1994

Daniel S. WELD, An Introduction to Least Commitment Planning, AI Magazine, Winter, 1994

AvaliaÁ“o

Brevemente aqui.

 

Material de Apoio

Projecções correspondentes à matéria do módulo: (PDF, 256k)

Projecções adicionais, com matérias não leccionadas no módulo mas na sequência dele: (PDF, 308k)

 

LigaÁžes

AI Subject Index - Planning and Scheduling Muitos links interessantes
CMU AI Repository - Planning and Plan Recognition Systems Muitos links interessantes
PLANET - European Network of Excellence in AI Planning PLANET is a coordinating organisation for European research and development in the field of Artificial Intelligence Planning and Scheduling and in particular aims to promote the transfer of this leading-edge technology into European industry. PLANET is a Network of Excellence funded by Esprit the European Information Technologies Programme.
AI Planning at the DFKI (German Research Center for Artificial Intelligence) On this page you will find some information about AI planning projects hosted by or in cooperation with the DFKI.
AI Planning and Scheduling Systems: Domain Repository (University of Maryland at College Park ) Hot Links and info for finding domain and/or operator specifications for AI planning and scheduling systems.
AI Research Group (University of Washigton) Alguns links interessantes. Particular atenção ao trabalho do Dan Weld.
Multiagent Planning Architecture (AI Center, SRI International, USA) A research project funded by the ARPA/Rome Laboratory Planning Initiative (ARPI). This page describes the Multiagent Planning Architecture as a research program within ARPI. More detail is available in the following documents. These are working papers and are modified frequently.
AI Planning Resources (NCSU, USA) This is a list of AI planners and where they were developed, or where implementations are currently accessible. Some of these places do a good deal of planning-related research, and of course this list is not exhaustive. I have however tried to include representative examples of the latest research directions, including Graphplan-oriented work and planning under uncertainty, as well as pointers to planners of historical interest.
Tutorial (Bryn Mawr College, USA) Tutorial on Planning by Deepak Kumar
UK Planning and Scheduling Interest Group The UK Planning SIG web-site is a focal point for information concerning SIG activities and resources. It contains information on companies, events, mailing lists, news, papers and publications, and people in the AI planning and scheduling field. In addition, there are links to many planning and scheduling systems.
Future Combat Systems (SRI Advanced Decision Architecture) Projectos na área militar
Small Unit Operations Planning & Decision Aids (SRI International, USA) Small Unit Operations Planning and Decision Aids will develop a planning and decision tool (PDA) for small unit operations (SUO). The key idea is that rich plan representations allow computers to share context with users, so both understand the semantics of plans and requests.
The UM Translog Planning Domain (University of Maryland at College Park ) The last twenty years of AI planning research has discovered a wide variety of planning techniques such as state-space search, hierarchical planning, case-based planning and reactive planning. These techniques have been implemented in numerous planning systems (STRIPS, SNLP, UCPOP, NONLIN, SIPE). Initially, a number of simple toy domains have been devised to assist in the analysis and evaluation of planning systems and techniques. The most well known examples are ``Blocks World'' and ``Towers of Hanoi.'' As planning systems grow in sophistication and capabilities, however, there is a clear need for planning benchmarks with matching complexity to evaluate those new features and capabilities. UM Translog is a planning domain designed specifically for this purpose.

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