PLANET Gap Bridging Seminar (GBS-2)

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PLANETGap Bridging Seminar (GBS-2)

• Prof. dr. Tim Grant
• Atos Origin Nederland / University of Pretoria
• Tim.Grant_at_atosorigin.com / tgrant_at_cs.up.ac.za

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Overview

• Presentation goal
• To introduce 2nd PLANET Gap-Bridging Seminar
• Structure
• Purpose of GBS-2
• Our sponsors
• EU Network of Excellence in Planning (PLANET)
• Features benefits analysis
• Introducing the speakers

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GBS-2 purpose (1)

• Motivation for GBS-2
• Academia industry both work in PS
• Their goals differ
• Academia
• Develops new knowledge technologies
• Performance measured in terms of publications
• Industry
• Applies knowledge technologies in products
  services
• Performance measured in financial terms
• Communications gap!

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GBS-2 purpose (2)

• GBS-2s aim
• To bridge the gap between academia industry
• Approach
• Industrial speakers talk about real-world
  applications
• Academic audience
• Benefits
• To audience
• Gain understanding of wider influences on PS
• Gain new problems insights that can guide RD
• To speakers
• Visibility, state-of-the-art, partnerships,
  recruitment

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GBS-2 sponsors

• PLANET
• EU Network of Excellence in AI Planning
• http//www.planet-noe.org/
• SIKS
• Dutch research school for Information Knowledge
  Systems
• http//www.siks.nl/
• TU Delft
• Leading Dutch university of technology
• http//www.tudelft.nl
• Atos Origin
• Leading international IT services provider
• http//www.atosorigin.com/

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PLANET (1)

• Overall aim
• Build co-ordinated network to support research,
  development, technology transfer in Europe
• Objectives
• Encourage pan-European co-operation between
  research groups industry
• Promote technology transfer by early involvement
  of industrial partners
• Co-ordinate training exchange of researchers
  and people from industry public administration
• Provide an information infrastructure and a
  representative source of expertise

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PLANET (2)

• Work packages

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PLANET (3)

• Activities
• General network meetings
• TCU meetings/workshops (often linked to
  conferences)
• Cross-site visits (between PLANET members)
• Information days (for industry)
• Summer schools (for students)
• Gap-bridging seminars
• Deliverables
• Software catalogue repository
• Benchmarks case studies
• Newsletters, posters, TCU flyers
• Annual reports
• PS curriculum
• Exploitation plan

All downloadable from http//www.planet-noe.org/
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PLANET (4)

• Technical Co-ordination Units (TCUs)
• Identify areas of current needs opportunities
  amongst PLANET members

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PLANET (5)

• TCU road-maps identify
• Current state of PS technology
• Recent developments
• Relationships to other fields
• Application problems deficiencies
• Technology transfer issues
• Directions for potential exploitation
• Application-driven improvements
• Plans for focussed actions

Downloadable from http//www.planet-noe.org/
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Features benefits (1)

• PLANET ends August 2003
• Now starting Exploitation Plan
• Short term (3 years)
• Medium term (6 years)
• Long term (10 years)
• Marketing analysis proposed to aid exploitation
• Stakeholder analysis
• Survey of European capabilities offerings
• SWOT analysis
• Features benefits analysis
• Marketing plan marketing materials

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Features benefits (2)
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Features benefits (3)

• Features benefits analysis
• Aim
• To define product / service in customers terms
• Feature
• What product / service has or is
• Benefit
• What product / service does for customer
• Analysis procedure
• Identify customer populations their needs
• Decide what product / service is to be sold
• Identify features that product / service provides
• Match features to benefits that customers obtain
• Prove that benefits can be delivered

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Features benefits (4)

• AI PS products services
• Some possible products
• Planning(-domain) knowledge acquisition software
• Plan-generation software
• Plan-animation software
• Plan-evaluation software
• Plan-execution software
• Plan-recognition software
• Some possible services
• Planning software selection, installation
  integration
• Tailoring planning software specific to domain
• Domain knowledge capture representation
• Plan execution, monitoring control

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Features benefits (5)

• Plan-generator can be
• Human
• Unaided
• Supported by non-intelligent software
• Spreadsheet, database, planning package
• Supported by intelligent software
  (mixed-initiative planning)
• Automation
• Hardware (invariably non-intelligent, e.g. PLCs)
• Non-intelligent software (canned responses)
• Intelligent software
• Comparisons
• Intelligent plan-generation software vs. human
• Intelligent plan-generation software vs. hardware
• Intelligent vs. non-intelligent plan-generation
  software

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Features benefits (6)

• Example features of plan-generator
• Functional
• It uses domain knowledge (including domain
  constraints)
• It can decompose goals
• It puts actions into sequences that meet domain
  constraints
• It generates sequences from initial to goal state
• It selects suitable (renewable) resources for
  actions
• It can reason at multiple levels of (domain)
  abstraction
• It can reason about concurrent action
• It can handle uncertain information
• Given same problem, it is guaranteed to produce
  same plan
• Non-functional
• It is tireless (24 hours/day, 365 days/year)
• It is reliable (e.g. 10-5 availability over one
  year)
• It works in real-time it can generate valid plan
  by a deadline
• It integrates to customers other IT systems
• It provides standard (system, user) interfaces

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Features benefits (7)

• Possible customer benefits
• Faster
• Installed and/or tailored more quickly
• Generates plan more quickly
• Updates plan more quickly after change
• Better
• Plans for more complex domains
• Generates better-quality plans (less
  domain-resource usage)
• Generates plans that have fewer errors
• Generates plans that are more robust to changes
• Cheaper
• Lower purchase cost
• Lower running costs
• Fewer operators needed
• Less operator training needed
• Less hardware / cheaper hardware

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Features benefits (8)

• Real-world proof
• Brian Drabble, University of Oregon/ OnTime Inc.
• Submarine construction (Electric Boat)
• 1.4 million tasks
• 30 reduction in overtime subcontracting
• Runtime 1 day instead of 6 weeks
• Aircraft construction (Boeing)
• 570 tasks, 17 resources
• 10-15 shorter, saving US1.2 million per
  aircraft
• Runtime 30 mins (2 orders of magnitude faster)
• ARPA Planning Initiative
• Logistics build-up to Gulf War, 1991
• Saved more than the cost of all US AI research
• Sources Cross Walker (1994) AIPS96

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GBS-2 speakers

• Alessandro Donati
• Space Mission Operations PS Past, present,
  future
• European Space Operations Centre
• http//www.esoc.esa.de
• Henk Hesselink
• AI Planning waiting for results?
• Dutch National Aerospace Laboratory (NLR)
• http//www.nlr.nl
• Frank Oxener
• Work Force Planning A logical next step after
  ERP
• Atos Origin Nederland b.v.
• http//www.atosorigin.com
• Yossi Rissin Roman Bartak
• When Theory Crashed into Reality
• Visopt b.v.
• http//www.visopt.com