2025-01-10 13:35:00
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{"algorithm":{"algorithm":{"currentFile":{"count":1,"lastUpdated":1736360369637}}},"computing":{"computing":{"currentFile":{"count":2,"lastUpdated":1736427522780}}},"tasks":{"tasks":{"currentFile":{"count":1,"lastUpdated":1736428160890}}},"parallelization":{"parallelization":{"currentFile":{"count":1,"lastUpdated":1736428239757}}},"Implicit":{"Implicit":{"currentFile":{"count":1,"lastUpdated":1736429811730}}},"Semi-implicit":{"Semi-implicit":{"currentFile":{"count":1,"lastUpdated":1736429857427}}},"Agent":{"Agent":{"currentFile":{"count":1,"lastUpdated":1736527234430}}},"Agents":{"Agents":{"currentFile":{"count":3,"lastUpdated":1736528265726}}},"actions":{"actions":{"currentFile":{"count":1,"lastUpdated":1736527553391}}},"successful":{"successful":{"currentFile":{"count":1,"lastUpdated":1736527687166}}},"agents":{"agents":{"currentFile":{"count":1,"lastUpdated":1736528222472}}},"environment":{"environment":{"currentFile":{"count":2,"lastUpdated":1736528276442}}},"actuators":{"actuators":{"currentFile":{"count":1,"lastUpdated":1736528278631}}},"Sensors":{"Sensors":{"currentFile":{"count":1,"lastUpdated":1736528280975}}}}
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{"algorithm":{"algorithm":{"currentFile":{"count":1,"lastUpdated":1736360369637}}},"computing":{"computing":{"currentFile":{"count":2,"lastUpdated":1736427522780}}},"tasks":{"tasks":{"currentFile":{"count":1,"lastUpdated":1736428160890}}},"parallelization":{"parallelization":{"currentFile":{"count":1,"lastUpdated":1736428239757}}},"Implicit":{"Implicit":{"currentFile":{"count":1,"lastUpdated":1736429811730}}},"Semi-implicit":{"Semi-implicit":{"currentFile":{"count":1,"lastUpdated":1736429857427}}},"Agent":{"Agent":{"currentFile":{"count":1,"lastUpdated":1736527234430}}},"Agents":{"Agents":{"currentFile":{"count":3,"lastUpdated":1736528265726}}},"actions":{"actions":{"currentFile":{"count":1,"lastUpdated":1736527553391}}},"successful":{"successful":{"currentFile":{"count":1,"lastUpdated":1736527687166}}},"agents":{"agents":{"currentFile":{"count":3,"lastUpdated":1736529446424}}},"environment":{"environment":{"currentFile":{"count":2,"lastUpdated":1736528276442}}},"actuators":{"actuators":{"currentFile":{"count":1,"lastUpdated":1736528278631}}},"Sensors":{"Sensors":{"currentFile":{"count":1,"lastUpdated":1736528280975}}},"state":{"state":{"currentFile":{"count":1,"lastUpdated":1736529437831}}},"types":{"types":{"currentFile":{"count":1,"lastUpdated":1736529458373}}}}
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@ -30,3 +30,9 @@ A rational agent is not omniscient or clairvoyant. It is not guaranteed they wil
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- Dynamic/static - If environment changes while an agent is deliberating
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- Dynamic/static - If environment changes while an agent is deliberating
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- Discrete/Continuous - State of the environment (states in chess vs taxi driving)
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- Discrete/Continuous - State of the environment (states in chess vs taxi driving)
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- Known/Unknown - In known environments, the outcomes for all given actions are given
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- Known/Unknown - In known environments, the outcomes for all given actions are given
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### Agent types
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- Simple reflex agents
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- Model based reflex agents with state
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- Goal-based agents
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- Utility based agents
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All of these can be turned into learning types
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