Artificial Entity Goal

An Artificial Entity Goal is an entity goal that guides a artificial entity towards achieving its Designed Objective through Programmed Behavior Patterns.

• AKA: Synthetic System Goal, Machine Goal Concept.
• Context:
  • Goal Input: System Design Objective, Entity Capability State, Goal Parameters
    • Optional Input: Goal Constraint Rules, System Boundary Conditions
  • Goal Output: Goal-Directed Actions, System Behavior Patterns, Achievement States
  • Goal Performance Measure: Goal Completion Metric, Achievement Success Rate, Objective Progress Level
  • ...
  • It can guide Artificial Behavior Patterns through Goal Achievement Processes.
  • It can structure System Decision Making through Goal Priority Framework.
  • It can define System Success Metrics through Goal Achievement Measures.
  • It can shape System Resource Allocation through Goal Requirement Patterns.
  • It can control System Action Selection through Goal Alignment Processes.
  • ...
  • It can often require Goal Progress Tracking through System Monitoring Framework.
  • It can often need Goal-Based Adjustment through System Feedback Process.
  • It can often involve Goal Resource Management through System Allocation Strategy.
  • It can often demand Goal Performance Assessment through System Evaluation Framework.
  • ...
  • It can range from being a Simple Machine Goal to being a Complex System Goal, depending on its Goal Complexity Level.
  • It can range from being a Single Entity Goal to being a Multi-Entity Goal, depending on its System Scope Level.
  • It can range from being a Task-Specific Goal to being a General Purpose Goal, depending on its Goal Generality Level.
  • It can range from being a Fixed System Goal to being an Adaptive System Goal, depending on its Goal Flexibility Level.
  • ...
  • It can integrate with Goal Planning Frameworks for System Action Coordination.
  • It can connect to Goal Control Mechanisms for System Behavior Regulation.
  • It can support Goal Learning Processes for System Objective Refinement.
  • It can enable Goal Adaptation Systems for System Objective Modification.
  • ...
• Examples:
  • Software System Goals, such as:
    • AI Goal Types, such as:
      • Machine Learning System Goal for Pattern Recognition Task.
      • Expert System Goal for Domain-Specific Task.
    • Agent Goal Types, such as:
      • BDI Agent Goal for Rational Behavior System.
      • Multi-Agent Goal for Collaborative System Task.
      • AI Self-Preservation.
  • Robotic System Goals, such as:
    • Physical Task Goals, such as:
      • Robot Movement Goal for Motion Control Task.
      • Robot Manipulation Goal for Object Interaction Task.
    • Mission Goals, such as:
      • Robot Operation Goal for Complex Task Sequence.
      • Robot Coordination Goal for Multi-Unit Task.
  • ...
• Counter-Examples:
  • Natural Entity Goal, which emerges from Biological System rather than Programmed Design.
  • Human Goal System, which involves Conscious Decision rather than Programmed Objective.
  • Emergent Behavior Pattern, which lacks Explicit Goal Definition.
  • Random System Action, which has no Goal Direction Process.
  • Environmental System State, which exists outside Goal Framework System.
• See: Artificial Goal System, Machine Behavior Pattern, System Goal Achievement, Programmed Action Planning, System Performance Framework, Goal Management System, Artificial Control Framework.

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