Difference between revisions of "Computational model"
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(Created page with " =Types of computational models= Below is a structured list of computational models. The spectrum is organized from fully deterministic and centralized at one end, to decentr...") |
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| − | !# !Model Type !Name !Key Properties !Position | + | !# |
| − | |- 1 || Deterministic || Finite State Machine (FSM) || Static states, input-driven transitions, no memory beyond state || Minimal autonomy, centralized | + | !Model Type |
| − | |- 2 || Deterministic || Pushdown Automaton (PDA) || FSM + stack (memory), suitable for parsing nested structures || FSM with memory | + | !Name |
| − | |- 3 || Deterministic || Turing Machine || Infinite tape memory, theoretical basis of general computation || Centralized but powerful | + | !Key Properties |
| − | |- 4 || Reactive Systems || Event-Driven Architectures (EDA) || Stateless or stateful, reacts to events, e.g., microcontrollers || Still centralized or module-local | + | !Position |
| − | |- 5 || Distributed State Machines || State Machine Replication (SMR) || FSMs replicated across nodes (e.g., Raft, Paxos), ensuring consistency || Blockchain consensus layer fits here | + | |- |
| − | |- 6 || Distributed Execution || Smart Contracts (on Blockchain) || FSM-like, deterministic, distributed, passive, consensus-driven || Bridges centralized logic and distributed deployment | + | |1 || Deterministic || Finite State Machine (FSM) || Static states, input-driven transitions, no memory beyond state || Minimal autonomy, centralized |
| − | |- 7 || Logic-based || Rule-Based Systems / Expert Systems || IF-THEN rules, possibly with a working memory || Central but symbolic reasoning | + | |- |
| − | |- 8 || Knowledge-based || Production Systems || Rule sets with inference engine and memory (e.g., OPS5, CLIPS) || Local reasoning; semi-autonomous | + | |2 || Deterministic || Pushdown Automaton (PDA) || FSM + stack (memory), suitable for parsing nested structures || FSM with memory |
| − | |- 9 || Object-Oriented || Actors Model || Concurrent entities with private state, communicate via async messages || Distributed, loosely coupled | + | |- |
| − | |- 10 || Declarative/Reactive Constraint Satisfaction Systems Solves problems by propagating constraints across variables || Reactive, can be distributed | + | |3 || Deterministic || Turing Machine || Infinite tape memory, theoretical basis of general computation || Centralized but powerful |
| − | |- 11 || Autonomous Agents || BDI Agents (Belief-Desire-Intention) || Agents with internal goals, beliefs, and planning || Autonomous, goal-directed | + | |- |
| − | |- 12 || Adaptive || Reinforcement Learning Agents || Learn behavior through environment interaction and reward || Adaptive, often centralized | + | |4 || Reactive Systems || Event-Driven Architectures (EDA) || Stateless or stateful, reacts to events, e.g., microcontrollers || Still centralized or module-local |
| − | |- 13 || Distributed Autonomous || Swarm Intelligence / Stigmergic Systems || Indirect coordination via environment (stigmergy), e.g., ant colony || Bottom-up emergence, no central control | + | |- |
| − | |- 14 || Distributed Coordination || Multi-Agent Systems (MAS) || Autonomous agents, possible learning, social protocols, communication || Fully distributed and adaptive | + | |5 || Distributed State Machines || State Machine Replication (SMR) || FSMs replicated across nodes (e.g., Raft, Paxos), ensuring consistency || Blockchain consensus layer fits here |
| − | |- 15 || Hybrid Adaptive || Cognitive Architectures (e.g., SOAR, ACT-R) || Integrates perception, planning, memory, learning || High autonomy, often hybrid centralized-distributed | + | |- |
| − | |- 16 || Decentralized Social Machines || Holonic Systems / Digital Ecosystems || Self-similar agents (holons), recursive coordination, adaptability || Edge of MAS and beyond | + | |6 || Distributed Execution || Smart Contracts (on Blockchain) || FSM-like, deterministic, distributed, passive, consensus-driven || Bridges centralized logic and distributed deployment |
| + | |- | ||
| + | |7 || Logic-based || Rule-Based Systems / Expert Systems || IF-THEN rules, possibly with a working memory || Central but symbolic reasoning | ||
| + | |- | ||
| + | |8 || Knowledge-based || Production Systems || Rule sets with inference engine and memory (e.g., OPS5, CLIPS) || Local reasoning; semi-autonomous | ||
| + | |- | ||
| + | |9 || Object-Oriented || Actors Model || Concurrent entities with private state, communicate via async messages || Distributed, loosely coupled | ||
| + | |- | ||
| + | |10 || Declarative/Reactive Constraint Satisfaction Systems ||Solves problems by propagating constraints across variables || Reactive, can be distributed | ||
| + | |- | ||
| + | |11 || Autonomous Agents || BDI Agents (Belief-Desire-Intention) || Agents with internal goals, beliefs, and planning || Autonomous, goal-directed | ||
| + | |- | ||
| + | |12 || Adaptive || Reinforcement Learning Agents || Learn behavior through environment interaction and reward || Adaptive, often centralized | ||
| + | |- | ||
| + | |13 || Distributed Autonomous || Swarm Intelligence / Stigmergic Systems || Indirect coordination via environment (stigmergy), e.g., ant colony || Bottom-up emergence, no central control | ||
| + | |- | ||
| + | |14 || Distributed Coordination || Multi-Agent Systems (MAS) || Autonomous agents, possible learning, social protocols, communication || Fully distributed and adaptive | ||
| + | |- | ||
| + | |15 || Hybrid Adaptive || Cognitive Architectures (e.g., SOAR, ACT-R) || Integrates perception, planning, memory, learning || High autonomy, often hybrid centralized-distributed | ||
| + | |- | ||
| + | |16 || Decentralized Social Machines || Holonic Systems / Digital Ecosystems || Self-similar agents (holons), recursive coordination, adaptability || Edge of MAS and beyond | ||
|} | |} | ||
Revision as of 23:21, 25 July 2025
Types of computational models
Below is a structured list of computational models. The spectrum is organized from fully deterministic and centralized at one end, to decentralized, adaptive, and emergent systems at the other.
| # | Model Type | Name | Key Properties | Position |
|---|---|---|---|---|
| 1 | Deterministic | Finite State Machine (FSM) | Static states, input-driven transitions, no memory beyond state | Minimal autonomy, centralized |
| 2 | Deterministic | Pushdown Automaton (PDA) | FSM + stack (memory), suitable for parsing nested structures | FSM with memory |
| 3 | Deterministic | Turing Machine | Infinite tape memory, theoretical basis of general computation | Centralized but powerful |
| 4 | Reactive Systems | Event-Driven Architectures (EDA) | Stateless or stateful, reacts to events, e.g., microcontrollers | Still centralized or module-local |
| 5 | Distributed State Machines | State Machine Replication (SMR) | FSMs replicated across nodes (e.g., Raft, Paxos), ensuring consistency | Blockchain consensus layer fits here |
| 6 | Distributed Execution | Smart Contracts (on Blockchain) | FSM-like, deterministic, distributed, passive, consensus-driven | Bridges centralized logic and distributed deployment |
| 7 | Logic-based | Rule-Based Systems / Expert Systems | IF-THEN rules, possibly with a working memory | Central but symbolic reasoning |
| 8 | Knowledge-based | Production Systems | Rule sets with inference engine and memory (e.g., OPS5, CLIPS) | Local reasoning; semi-autonomous |
| 9 | Object-Oriented | Actors Model | Concurrent entities with private state, communicate via async messages | Distributed, loosely coupled |
| 10 | Declarative/Reactive Constraint Satisfaction Systems | Solves problems by propagating constraints across variables | Reactive, can be distributed | |
| 11 | Autonomous Agents | BDI Agents (Belief-Desire-Intention) | Agents with internal goals, beliefs, and planning | Autonomous, goal-directed |
| 12 | Adaptive | Reinforcement Learning Agents | Learn behavior through environment interaction and reward | Adaptive, often centralized |
| 13 | Distributed Autonomous | Swarm Intelligence / Stigmergic Systems | Indirect coordination via environment (stigmergy), e.g., ant colony | Bottom-up emergence, no central control |
| 14 | Distributed Coordination | Multi-Agent Systems (MAS) | Autonomous agents, possible learning, social protocols, communication | Fully distributed and adaptive |
| 15 | Hybrid Adaptive | Cognitive Architectures (e.g., SOAR, ACT-R) | Integrates perception, planning, memory, learning | High autonomy, often hybrid centralized-distributed |
| 16 | Decentralized Social Machines | Holonic Systems / Digital Ecosystems | Self-similar agents (holons), recursive coordination, adaptability | Edge of MAS and beyond |