Understanding Agent Models: Agents, Reactivity, Pro-activeness, and Agenda, Slides of Multiagent Systems

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Agent models.

Basic agent model

• An agent is a triplet of A = <Ag, KB, S>
• Ag: agenda. The things the agent wants to accomplish.
  • Can be defined as a function of the knowledgebase Ag = Ag(KB)
  • Also known as: goal
• KB: knowledgebase. The sum of the knowledge of the agent about its environment and itself. - Also known as: state, model of the world
• S: strategy. -Action = S(KB, Ag) -Also known as: behavior -The strategy of the agent generates actions based on the knowledgebase and the agenda.

Pro-activeness

• Reacting to the environment is easy (e.g. stimulus-> response rules)
• But we generally want agents to do things for us.
• Hence: goal directed behavior.
• Pro-activeness = generating and attempting to achieve goals; not driven solely by events, taking the initiative.
• Recognizing opportunities.

Purely reactive agent

• Purely reactive agent
  • No knowledgebase / No state
  • The knowledge of the agent is restricted to the most recent sensor input
  • Easily expressible as
    • Action-reaction tables
    • Rule-sets
  • The behavior of the agent does not depend on its history
  • E.g. thermostat

Agent Building Problem

• We call the states of the world where the agenda is satisfied desired state of the world.
• Given a agenda Ag and an initial set of knowledge KB 0 create a strategy S which “works towards” the agenda.
• In general, when designing agents:
  • The agenda is a given in the specification of the agent
  • The initial knowledge is given (but the agent builder frequently needs to work to achieve a good knowledge representation)
  • The strategy needs to be created by the agent builder
  • The knowledge of the agent needs to be gathered by the agent builder.

Pitfall: Self deceiving agents

• While we are talking about a desired state of the world, the agenda is defined on the knowledgebase, not on the world
• The easiest way for an agent to satisfy the agenda is to change only the knowledgebase. It is so much easier than bothering with the world!
• There is no automatic guarantee that the knowledgebase is accurate.
• Solution:
  • The agent needs to take explicit actions to update and refresh the knowledgebase.
  • It is better to update the knowledgebase based on the feedback from the environment, instead of the predicted effect of the action.

Perception / Sensing

• Perception is a special kind of action, performed by an agent to update its knowledgebase.
• A perception is valid, if after the perception, the knowledgebase is a better approximation of the world than before.
• A perception is pure if the changes contained by it apply exclusively to the knowledgebase. - It is difficult to achieve a pure perception (see the Heisenberg uncertainty principle) Docsity.com

Implementing strategies

• Strategies are the active component of any agent.
• It is very difficult to just sit down and implement a monolitic strategy which encapsulates the whole functionality of the agent.
• The first, pragmatic step is to decompose the strategies.
• At some point, we cannot decompose further, so we actually need to start implementing it:Docsity.com