Utility-Based Agent

A Utility-Based Agent is a goal-based agent that uses utility functions to evaluate and select optimal actions.

• AKA: Rational Agent, Decision-Theoretic Agent, Expected Utility Agent.
• Context:
  • It can typically calculate Utility-Based Agent Expected Utility for utility-based agent action alternatives.
  • It can typically maximize Utility-Based Agent Utility Values in utility-based agent decision making.
  • It can typically compare Utility-Based Agent Outcomes using utility-based agent preference ordering.
  • ...
  • It can often handle Utility-Based Agent Uncertainty through utility-based agent probabilistic reasoning.
  • It can often balance Utility-Based Agent Multiple Objectives via utility-based agent utility combination.
  • It can often adapt Utility-Based Agent Utility Functions based on utility-based agent preference learning.
  • ...
  • It can range from being a Simple Utility-Based Agent to being a Complex Utility-Based Agent, depending on its utility-based agent function sophistication.
  • It can range from being a Risk-Neutral Utility-Based Agent to being a Risk-Averse Utility-Based Agent, depending on its utility-based agent risk preference.
  • It can range from being a Single-Attribute Utility-Based Agent to being a Multi-Attribute Utility-Based Agent, depending on its utility-based agent evaluation dimensions.
  • It can range from being a Myopic Utility-Based Agent to being a Forward-Looking Utility-Based Agent, depending on its utility-based agent temporal consideration.
  • ...
  • It can integrate with Utility-Based Agent Decision Theory Frameworks for utility-based agent optimal choice.
  • It can connect to Utility-Based Agent Probability Models for utility-based agent outcome prediction.
  • ...
• Example(s):
  • Economic Utility-Based Agents, such as:
    • Market Trading Utility-Based Agent maximizing utility-based agent profit.
    • Resource Allocation Utility-Based Agent optimizing utility-based agent efficiency.
  • Game-Theoretic Utility-Based Agents, such as:
    • Nash Equilibrium Utility-Based Agent in utility-based agent strategic interactions.
    • Minimax Utility-Based Agent for utility-based agent adversarial settings.
  • Multi-Criteria Utility-Based Agents, such as:
    • Weighted Sum Utility-Based Agent combining utility-based agent multiple criterions.
    • Pareto-Optimal Utility-Based Agent balancing utility-based agent competing objectives.
  • ...
• Counter-Example(s):
  • Goal-Based Agent, which lacks utility-based agent quantitative evaluation.
  • Satisficing Agent, which seeks utility-based agent adequate solutions rather than optimal ones.
  • Rule-Based Agent, which follows utility-based agent fixed rules without utility calculation.
• See: Goal-Based Agent, Decision Theory, Expected Utility Theory, Rational Choice Theory, Multi-Objective Optimization, Game Theory, Preference Learning.

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