From 1d2853cc1359c000f27c56c5b00643bdf7261712 Mon Sep 17 00:00:00 2001 From: Isaac Shoebottom Date: Fri, 10 Jan 2025 13:15:28 -0400 Subject: [PATCH] 2025-01-10 13:15:28 --- .../various-complements/histories.json | 2 +- .obsidian/workspace.json | 7 ++-- UNB/Year 5/Semester 2/CS4725/Lecture Notes.md | 32 +++++++++++++++++++ 3 files changed, 37 insertions(+), 4 deletions(-) create mode 100644 UNB/Year 5/Semester 2/CS4725/Lecture Notes.md diff --git a/.obsidian/plugins/various-complements/histories.json b/.obsidian/plugins/various-complements/histories.json index 0545f60..77a2ee6 100644 --- a/.obsidian/plugins/various-complements/histories.json +++ b/.obsidian/plugins/various-complements/histories.json @@ -1 +1 @@ -{"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}}}} \ No newline at end of file +{"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}}}} \ No newline at end of file diff --git a/.obsidian/workspace.json b/.obsidian/workspace.json index c9cf49f..cbebaf6 100644 --- a/.obsidian/workspace.json +++ b/.obsidian/workspace.json @@ -13,7 +13,7 @@ "state": { "type": "markdown", "state": { - "file": "UNB/Year 5/Semester 2/CS4613/Lecture Notes.md", + "file": "UNB/Year 5/Semester 2/CS4725/Lecture Notes.md", "mode": "source", "source": false }, @@ -168,6 +168,8 @@ "active": "a4868a0d0ec2cb3a", "lastOpenFiles": [ "UNB/Year 5/Semester 2/CS4745/Lecture Notes.md", + "UNB/Year 5/Semester 2/CS4725/Lecture Notes.md", + "UNB/Year 5/Semester 2/CS4725", "UNB/Year 5/Semester 2/CS4613/Lecture Notes.md", "UNB/Year 5/Semester 2/CS4613", "UNB/Year 5/Semester 2/CS4745", @@ -192,7 +194,6 @@ "UNB/Year 5/Semester 1/MAAC3113", "UNB/Year 5/Semester 1/HIST1451/Political questionaire.md", "UNB/Year 5/Semester 1/CS3113", - "UNB/Year 5/Semester 1/HIST1001", - "UNB/Year 5/Semester 1/HIST1451" + "UNB/Year 5/Semester 1/HIST1001" ] } \ No newline at end of file diff --git a/UNB/Year 5/Semester 2/CS4725/Lecture Notes.md b/UNB/Year 5/Semester 2/CS4725/Lecture Notes.md new file mode 100644 index 0000000..6cfee65 --- /dev/null +++ b/UNB/Year 5/Semester 2/CS4725/Lecture Notes.md @@ -0,0 +1,32 @@ +## AI Agents +AI agents are defined as a program (state of all previous actions and inputs) that produces an agent function + +### Reflex Vacuum Cleaner Agent +Essentially a rules table, based on the state of the environment and the agent, (state of dirt in a/b, position of cleaner in a or b) +### Rational Agents +A fixed performance measure the agent should set as their goal, based on the environment and the agents actions +- One point per square cleaned in time T? +- One point per clean square per time step, minus one per move? +- Penalize for > k dirty moves? +A rational agent chooses the action that maximizes the expected value of the performance measure given the percept sequence to date. + +A rational agent is not omniscient or clairvoyant. It is not guaranteed they will perceive everything relevant, or are given the relevant information. They also may not be successful in the action as expected. A rational agent does not mean a successful one. +### Defining internet agents +#### Automated Taxi +- Performance measure +- environment +- actuators +- sensors +#### Internet Shopping Agent +- Performance measure +- environment +- actuators +- Sensors +### Task environment characteristics +- Fully/Partially observable - Agents sensors give it access to complete state of the environment at each point in time +- Single/multi-agent - Single agent solving a problem (puzzle vs chess) +- Deterministic/Non-deterministic - Whatever next state is determined completely by the current state, ie randomness +- Episodic/sequential - Agent's experience divided into atomic episode (agent receives a percept and perform a single action) +- Dynamic/static - If environment changes while an agent is deliberating +- Discrete/Continuous - State of the environment (states in chess vs taxi driving) +- Known/Unknown - In known environments, the outcomes for all given actions are given \ No newline at end of file