AN OVERVIEW OF AGENT BASED PARADIGMS AND ENTERPRISE SIMULATION FOR ELEARNING AND KNOWLEDGE TRANSMISS

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AN OVERVIEW OF AGENT BASED PARADIGMS AND
ENTERPRISE SIMULATION FOR E-LEARNING AND
KNOWLEDGE TRANSMISSION

• Marco Remondino
• remond_at_di.unito.it
• University of Turin, Italy

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We will deal with

• methodologies for designing models of interactive
  simulation, based on software (artificial) agents
• to be used for education and in general for
  knowledge transmission through e-learning
  techniques

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E-LEARNING

• The term e-learning refers to the use of
  computers and related technologies, such as
  networks, multimedia and so on, for educational
  purposes
• A model is built, representing some real
  situation in which the learners can take
  decisions and see the corresponding results.

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Two Agent Based Paradigms

• Reactive Agents
• No internal representation of the environment
• When to act? What action to choose?
• Aggregate behaviour (consequence)
• Cognitive Agents
• Presence of high level goals
• Behaviour as a consequence
• Learning by trial error

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Action Selection and RL

• action selection problem at time t1
• How to select an action?
• Reinforcement Learning turning a quantitative
  value (payoff) into behavioural pattern

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How to Select an Action?

• Q-Learning like algorithms (expected value
  function for each action)
• Agents wellbeing metaphor (internal drive
  external stimuli)
• Evolutionary Algorithms (aggregate level
  natural selection)

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Interactive Enterprise Simulation

• An implementation of virtual tutoring by
  intelligent agents
• Learners (tipically students) can practice the
  model
• Knowledge transfer is maieutical

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Management Game Vs Virtual Tutoring

• A management game is one in which the player
  takes decisions and observes final results
• A virtual tutoring system is similar, but with
  the addition of some entities, able to aid him
  finding the right patterns (simulated decision
  support system)

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An Operative Example

• http//e-lab.di.unito.it/SimulazioneAziendale
• An advanced management game (using System
  Dynamics)
• Now developing a framework of virtual tutoring,
  with intelligent agents (beta stage)

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You Take the Decisions
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You Observe the Results
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..and the Agent can give hints and explanations

• Hints
• Your production capacity is too low, improve it
• Explanations
• Profit went down since your production capacity
  is too low

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How to do that?

• Sentences are actions for the agents, to be
  selected via a Q-Learning like mechanism, with
  the model parameters as input
• Agents practice the model and find the best
  action to choose, according to the observed
  patterns

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Another Point of View

• Besides being used as a Virtual Tutoring System,
  intelligent agents can be part of the model
  itself
• Social systems are complex and not always
  deterministic agents can be the building blocks
  for them

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Data Base Security

• A framework to explain and teach the basic
  parameters of DBS
• We have a set of agents, which are the users of a
  database, organized into a hierarchy
• The learner is the DB manager and can change some
  core parameters

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The Learner can

• Change the privileges on data, for the different
  levels of users, keeping in mind that
• High level users have less chance to corrupt data
• The number of low level users is higher, so they
  need to access the data more frequently

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Data Integrity Vs Efficiency

• The user must change the parameters in order to
  find the optimal tradeoff

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Time for Accessing a Datum

• Flexible (unsecure) situation
• Read and Write privileges are always given
• Unflexible (secure) situation
• The permission must be asked to higher levels and
  so on. Time is

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Conclusion

• Intelligent Agents to be used for E-Learning and
  knowledge transmission
• Virtual Tutoring Systems and Management Games
• ABS frameworks to experience on simulated social
  systems

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Thank you!

• Thank you for your attention
• This presentation is also a proposal for
  interaction
• Email remond_at_di.unito.it