Cognitive Agent

A Cognitive Agent is an intelligent agent that can perform cognitive processes (to enable mental functions and thought operations).

AKA: Mental Entity.
Context:
- It can (typically) maintain Cognitive States through cognitive mental conditions and cognitive thought states.
- It can (typically) perform Cognitive Actions via cognitive mental execution and cognitive intentional operations.
- It can (typically) process Cognitive Information through cognitive information analysis, cognitive memory encoding, and cognitive perceptual interpretation.
- It can (typically) develop Cognitive Models of cognitive environments using cognitive representational structures.
- It can (typically) contain a Cognitive Inductive Reasoning System for cognitive pattern recognition and cognitive generalization formation.
- It can (typically) contain a Cognitive Deductive Reasoning System for cognitive logical inference and cognitive rule application.
- It can (typically) have a Cognitive Learning Ability for cognitive knowledge acquisition through cognitive experience integration.
- It can (typically) have a Cognitive System for cognitive information processing with cognitive architectural components.
- It can (typically) demonstrate Cognitive Processing Capability in cognitive mental operations requiring cognitive attentional resources.
- It can (typically) possess Cognitive Storage Capacity in cognitive memory functions with varying cognitive retention durations.
- It can (typically) form Cognitive Connection Patterns in cognitive networks through cognitive associative mechanisms.
- It can (typically) manipulate Cognitive Representations through cognitive information transformation and cognitive symbolic processing.
- It can (typically) engage in Cognitive Information Acquisition through cognitive sensory processes and cognitive perceptual systems.
- It can (typically) implement Cognitive Goal-Directed Behavior through cognitive planning processes and cognitive intention formation.
- It can (typically) maintain Cognitive Internal States that influence cognitive decision outcomes.
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- It can (often) adapt Cognitive Patterns through cognitive adjustment based on cognitive feedback mechanisms.
- It can (often) modify Cognitive Structures via cognitive reorganization during cognitive development phases.
- It can (often) enhance Cognitive Performance through cognitive learning and cognitive practice optimization.
- It can (often) engage in Cognitive Reasoning through cognitive logical processes and cognitive inference chains.
- It can (often) achieve Cognitive Awareness of cognitive states and cognitive environments via cognitive monitoring systems.
- It can (often) contain a Cognitive Abductive Reasoning System for cognitive hypothesis generation and cognitive explanation formation.
- It can (often) be supported by a Cognitive Operating System for cognitive mental operations and cognitive resource allocation.
- It can (often) make Cognitive Decisions that lead to Cognitive Actions through cognitive evaluation processes.
- It can (often) be a Cognitive Linguistic Agent capable of cognitive symbol manipulation and cognitive language processing.
- It can (often) develop Cognitive Mental Models of its cognitive environment through cognitive observation integration.
- It can (often) engage in Cognitive Restructuring to adapt cognitive belief patterns when confronted with cognitive contradictory evidence.
- It can (often) apply Cognitive Chunking to optimize cognitive information processing by grouping cognitive related elements.
- It can (often) demonstrate Cognitive Abstraction to simplify cognitive representations across cognitive complexity levels.
- It can (often) utilize Cognitive Modular Processing for cognitive specialized functions in cognitive domain-specific tasks.
- It can (often) participate in Cognitive Distributed Systems across cognitive collective structures to achieve cognitive emergent capabilitys.
- It can (often) implement Cognitive Prediction Systems to anticipate cognitive future states based on cognitive current conditions.
- It can (often) maintain Cognitive Homeostasis by regulating cognitive internal parameters within cognitive optimal ranges.
- It can (often) deploy Cognitive Resource Allocation Strategys to manage cognitive limited capacity.
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- It can range from being a Simple Cognitive Agent to being a Complex Cognitive Agent, depending on its cognitive complexity.
- It can range from being a Basic Cognitive Agent to being an Advanced Cognitive Agent, depending on its cognitive functional sophistication.
- It can range from being a Concrete Cognitive Agent to being an Abstract Cognitive Agent, depending on its cognitive abstraction level.
- It can range from being a Temporary Cognitive Agent to being a Permanent Cognitive Agent, depending on its cognitive temporal stability.
- It can range from being a Local Cognitive Agent to being a Distributed Cognitive Agent, depending on its cognitive distribution.
- It can range from being a Natural Cognitive Agent to being a Synthetic Cognitive Agent, depending on its cognitive implementation type.
- It can range from being an Accessible Cognitive Agent to being an Inaccessible Cognitive Agent, depending on its cognitive conscious awareness availability.
- It can range from being a Symbolic Cognitive Agent to being a Subsymbolic Cognitive Agent, depending on its cognitive representational format.
- It can range from being a Conscious Cognitive Agent to being a Non-Conscious Cognitive Agent, depending on its cognitive consciousness level.
- It can range from being a Living Cognitive Agent to being a Mechanical Cognitive Agent, depending on its cognitive implementation substrate.
- It can range from being an Emotional Cognitive Agent to being a Non-Emotional Cognitive Agent, depending on its cognitive emotional capacity.
- It can range from being a Single Domain Cognitive Agent to being a General Intelligence Cognitive Agent, depending on its cognitive domain breadth.
- It can range from being an Autonomous Cognitive Agent to being a Dependent Cognitive Agent, depending on its cognitive independence level.
- It can range from being a Fixed Cognitive Agent to being an Adaptive Cognitive Agent, depending on its cognitive learning capability.
- It can range from being an Individual Cognitive Agent to being a Collective Cognitive Agent, depending on its cognitive entity distribution.
- It can range from being a Static Cognitive Agent to being a Dynamic Cognitive Agent, depending on its cognitive adaptability rate.
- It can range from being a Specialized Cognitive Agent to being a Generalized Cognitive Agent, depending on its cognitive functional diversity.
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- It can interact with other Cognitive Agents through cognitive interaction mechanisms and cognitive communication protocols.
- It can participate in Cognitive Systems as cognitive components with defined cognitive functional roles.
- It can contribute to Cognitive Architectures as cognitive building blocks with specific cognitive architectural purposes.
- It can facilitate Cognitive Processes through cognitive operations and cognitive functional execution.
- It can express Cognitive Content through cognitive mental representations and cognitive knowledge structures.
- It can exist within Cognitive Domains at various cognitive levels of cognitive organizational hierarchy.
- It can have a Cognitive Skill Level in various cognitive domains based on cognitive expertise development.
- It can be a Cognitive Introspecting System with cognitive self-awareness and cognitive metacognitive capability.
- It can have Cognitive Personal Interests driving cognitive motivation and cognitive attention allocation.
- It can have a Cognitive Bias affecting cognitive decision making and cognitive judgment formation.
- It can possess Cognitive Theory of Mind for cognitive social cognition and cognitive mental state attribution.
- It can develop Cognitive Learning Strategys for cognitive skill acquisition and cognitive knowledge refinement.
- It can engage in Cognitive Chunking Processes to optimize cognitive memory utilization and cognitive information recall.
- It can form Cognitive Cohesive Units through cognitive information integration and cognitive conceptual binding.
- It can exhibit Cognitive Modularity through cognitive specialized processing in distinct cognitive functional modules.
- It can demonstrate Cognitive Adaptability in response to cognitive environmental changes through cognitive flexible response.
- It can utilize Cognitive Categorical Structures for cognitive information organization and cognitive conceptual classification.
- It can implement Cognitive Predictive Coding to minimize cognitive prediction error and optimize cognitive processing efficiency.
- It can establish Cognitive Temporal Models to represent cognitive event sequences and cognitive causal relationships.
- It can maintain Cognitive Context Awareness to appropriately adjust cognitive behavioral responses to cognitive situational factors.
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Examples:
- Cognitive Agent Types by function, such as:
  - Worker Cognitive Agents, performing cognitive work tasks and maintaining cognitive goal-directed behavior for cognitive productivity.
  - Reasoning Cognitive Agents, engaging in cognitive reasoning processes and demonstrating cognitive logical inference through cognitive deductive reasoning systems.
  - Aware Cognitive Agents, maintaining cognitive awareness states and utilizing cognitive monitoring systems for cognitive self-regulation.
  - Concept Cognitive Agents, representing cognitive conceptual knowledge and forming cognitive categorical structures for cognitive information organization.
  - Memory Cognitive Agents, facilitating cognitive memory functions and applying cognitive chunking for cognitive information processing.
  - Decision-Making Cognitive Agents, executing cognitive choice processes through cognitive evaluation of cognitive alternatives.
  - Learning Cognitive Agents, adapting through cognitive learning processes and developing cognitive learning strategys.
  - Problem-Solving Cognitive Agents, addressing cognitive challenge scenarios through cognitive solution generation and cognitive option evaluation.
  - Planning Cognitive Agents, creating cognitive action sequences to achieve cognitive goal states through cognitive temporal models.
  - Communication Cognitive Agents, enabling cognitive information exchange through cognitive linguistic processing.
- Cognitive Agent Types by implementation, such as:
  - Biological Cognitive Agents, such as:
    - Human Cognitive Agents with cognitive natural intelligence demonstrating cognitive consciousness and cognitive self-awareness.
    - Higher Primate Cognitive Agents with cognitive capabilitys including cognitive tool use and cognitive social learning.
    - Dolphin Cognitive Agents demonstrating cognitive problem solving and cognitive social intelligence.
    - Human Memory Cognitive Agent for human cognitive memory functions including cognitive episodic memory and cognitive semantic memory.
    - Human Reasoning Cognitive Agent for human cognitive reasoning processes utilizing cognitive inductive reasoning and cognitive deductive reasoning.
    - Human Perception Cognitive Agent for human cognitive sensory processing across cognitive sensory channels.
    - Corvid Cognitive Agent demonstrating avian cognitive tool use and cognitive causal understanding.
    - Elephant Cognitive Agent exhibiting cognitive social memory and cognitive empathic response.
  - Artificial Cognitive Agents, such as:
    - Advanced AI Cognitive Agents with cognitive learning capabilitys through cognitive neural architectures.
    - Autonomous Robot Cognitive Agents with cognitive decision making in cognitive physical environments.
    - Expert System Cognitive Agents in cognitive specialized domains utilizing cognitive rule-based reasoning.
    - Neural Network Cognitive Agent for artificial cognitive neural processing with cognitive pattern recognition.
    - Symbolic AI Cognitive Agent for logic-based cognitive reasoning using cognitive symbolic representations.
    - Hybrid Cognitive Agent for multi-paradigm cognitive processing combining cognitive symbolic systems and cognitive subsymbolic systems.
    - Large Language Model Cognitive Agent implementing cognitive linguistic processing and cognitive information retrieval.
    - Reinforcement Learning Cognitive Agent developing cognitive behavioral policys through cognitive reward-based learning.
  - Hybrid Cognitive Agents, such as:
    - Augmented Human Cognitive Agents with cognitive enhancements through cognitive technological extensions.
    - Brain-Computer Interface Cognitive Agents for cognitive augmentation via cognitive neural connections.
    - Distributed Intelligence Cognitive Agents forming cognitive networks through cognitive collaborative processing.
    - Cyborg Cognitive Agent with integrated cognitive biological-mechanical systems.
    - Enhanced Memory Cognitive Agent utilizing cognitive external storage to extend cognitive memory capacity.
  - Distributed Cognitive Agents, such as:
    - Collective Intelligence Cognitive Agent for group cognitive functions through cognitive collaborative mechanisms.
    - Swarm Cognitive Agent for emergent cognitive behavior from cognitive simple agent interactions.
    - Social Network Cognitive Agent for distributed cognitive processing across cognitive human networks.
    - Multi-Agent System Cognitive Agent implementing cognitive coordinated behavior through cognitive communication protocols.
    - Organizational Cognitive Agent representing cognitive institutional intelligence through cognitive structured processes.
- Cognitive Agent States, such as:
  - Conscious Cognitive Agents, maintaining conscious cognitive mental states with cognitive awareness and cognitive reflective capability.
  - Subconscious Cognitive Agents, operating below conscious cognitive awareness while influencing cognitive behavior.
  - Unconscious Cognitive Agents, functioning without conscious cognitive control through cognitive automatic processes.
  - Focus Cognitive Agents, directing cognitive attentional resources toward cognitive prioritized information.
  - Relaxed Cognitive Agents, enabling cognitive creative processes through cognitive diffuse attention.
  - Flow Cognitive Agents, achieving cognitive optimal performance states through cognitive immersive engagement.
  - Learning State Cognitive Agent undergoing cognitive knowledge acquisition through cognitive error correction.
  - Resting State Cognitive Agent performing cognitive default mode processing and cognitive memory consolidation.
- Cognitive Agent Types by mental function, such as:
  - Memory Cognitive Agents, such as:
  - Processing Cognitive Agents, such as:
  - Emotional Cognitive Agents, such as:
    - Affective Cognitive Agent for emotional cognitive state processing and cognitive feeling generation.
    - Mood Cognitive Agent for persistent cognitive emotional condition influencing cognitive interpretation bias.
    - Emotional Regulation Cognitive Agent for cognitive emotional balance through cognitive emotional control strategys.
    - Fear Cognitive Agent implementing cognitive threat detection and cognitive protective response.
    - Reward Cognitive Agent processing cognitive pleasure signals and cognitive motivation enhancement.
- Cognitive Agent Types by complexity, such as:
  - Elementary Cognitive Agents, such as:
    - Concept Cognitive Agent for conceptual cognitive representation of cognitive semantic meaning.
    - Schema Cognitive Agent for cognitive knowledge structure organization of cognitive related concepts.
    - Rule Cognitive Agent for cognitive procedural knowledge implementation through cognitive if-then structures.
    - Feature Detector Cognitive Agent identifying cognitive specific patterns in cognitive perceptual input.
    - Perceptual Primitive Cognitive Agent processing cognitive basic sensory elements.
  - Compound Cognitive Agents, such as:
    - Belief System Cognitive Agent for interconnected cognitive belief structures organizing cognitive worldview elements.
    - Knowledge Network Cognitive Agent for interrelated cognitive knowledge elements with cognitive semantic connections.
    - Mental Model Cognitive Agent for integrated cognitive understanding structures representing cognitive complex domains.
    - Narrative Cognitive Agent constructing cognitive story structures from cognitive sequential elements.
    - Social Understanding Cognitive Agent integrating cognitive interpersonal knowledge into cognitive social frameworks.
- Cognitive Agent Types by abstraction, such as:
  - Concrete Cognitive Agents, processing concrete cognitive representations tied to cognitive specific instances.
  - Abstract Cognitive Agents, handling abstract cognitive concepts independent of cognitive specific examples.
  - Meta-Cognitive Agents, engaging in cognitive self-reflective processes to monitor cognitive own functions.
  - Hypothetical Cognitive Agent manipulating cognitive counterfactual scenarios and cognitive possibility spaces.
  - Categorical Cognitive Agent organizing cognitive taxonomic structures and cognitive hierarchical classifications.
- Cognitive Agent Types by temporal orientation, such as:
  - Retrospective Cognitive Agent processing cognitive past experiences and cognitive historical information.
  - Present-Focused Cognitive Agent managing cognitive current states and cognitive immediate responses.
  - Prospective Cognitive Agent generating cognitive future projections and cognitive anticipatory models.
  - Multi-temporal Cognitive Agent integrating cognitive past-present-future connections for cognitive contextual understanding.
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Counter-Examples:
- Intelligent Entity, which can include non-cognitive intelligence forms such as swarm intelligence or emergent intelligence.
- Non-cognitive Intelligent Agent, which demonstrates intelligent behavior without cognitive processing.
- Physical Neural Structure, which provides physical substrate for cognitive agents but lacks integrated processing capability.
- Data Structure, which may store cognitive information but cannot actively perform cognitive functions.
- Information Processing System, which executes algorithmic operations without cognitive characteristics.
- Passive Knowledge Repository, which contains knowledge content but cannot engage in cognitive processes.
- Reactive System without cognitive internal representations.
- Simple Reflex Agent with fixed cognitive response patterns.
- Instinct-Driven Organism without cognitive learning capabilitys.
- Basic Tool without cognitive adaptive behavior.
- Static Program without cognitive decision making.
- Cognitive Module, which is a component of a cognitive agent rather than an agent itself.
- Cognitive Network, which is a structure formed by cognitive agents rather than being an agent itself.
- Mental Representation, which is a product created by cognitive agents rather than being an agent itself.
See: Intelligent Entity, Cognition, Cognitive System, Cognitive Process, Mental State, Cognitive Action, Conscious Mental State, Abstract Entity, Intelligent Agent, Cognitive Architecture, Mind, Intelligence Type, Learning System, Decision Making Process, Knowledge Representation, Adaptive Behavior, Embodied Cognition, Cognitive Development, Cognitive Module, Distributed Cognition, Cognitive Restructuring, Cognitive Complexity, Cognitive Abstraction, Cognitive Unit, Cognitive Chunking, Metacognition, Predictive Processing, Neural Network, Theory of Mind, Embodied Cognition, Extended Mind.

References

2009

(Berg-Cross, 2009) ⇒ Gary Berg-Cross. (2009). “Is An Agent Theory of Mind (ToM) Valuable for Adaptive, Intelligent Systems?.” In: Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems. doi:10.1145/1865909.1865936
- QUOTE: Formalized as a ToM theory these propose alternative inherited or acquired paths by which a particular cognitive capacity may arise in a cognitive agent (children) so they understand and predict external behavior of others by attributing unobservable mental states, such as beliefs, desires and intentions.

2002

(Riegler, 2002) ⇒ Alexander Riegler. (2002). “When is a Cognitive System Embodied?.” In: Cognitive Systems Research Journal, 3(3). doi:10.1016/S1389-0417(02)00046-3
- QUOTE: For cognitive systems, embodiment appears to be of crucial importance.