Answers.Body: <p>Why do you want to think of these algorithms as agents? </p>
  
  <p>An agent is an abstract and higher-level concept than the concept of an algorithm, which is just a set of instructions. </p>
  
  <p>You could have two agents, one that is supposed to find the minimum spanning tree and another that is supposed to find the shortest path between a source and goal nodes.  In both cases, these two agents have a goal, so they are both goal-oriented agents, but the algorithms they use to reach the goal are irrelevant, as long as they have one or more goals. If you have an agent that performs optimally with respect to some metric, you may want to call that agent an optimal agent.</p>
  
  <p>A similar logic applies to utility-based agents.</p>
  
  <p>So, in short, algorithms are used by agents to act, but the algorithms themselves are not the agents (unless you want to have a philosophical debate or use different definitions of agents). See <a href="https://ai.stackexchange.com/a/12995/2444">this answer</a> for more details about the definition of agents.</p>
  
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Answers.CreationDate: 2020-04-27T12:45:56.113Z
Answers.LastActivityDate: 2020-04-27T12:45:56.113Z
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Body: <p>From the perspective of the type of AI Agents, I would like to discuss Prim's Minimum Spanning Tree algorithm and Dijkstra's Algorithm.</p>
  <p>Both are model-based agents and both are &quot;greedy algorithms&quot;.</p>
  <p>Both have their memory to store the history of vertices and their path distance. Prim's is <strong>more greedy</strong> than Dijkstra's algorithm whereas Dijkstra's algorithm is <strong>more efficient</strong> than Prim's.</p>
  <p>Can we say that Dijkstra's algorithm is a utility-based agent, whereas Prim's is a goal-based agent, with the justification that Prim's is <strong>more goal-oriented</strong> as compared to finding the optimum (shortest) path?</p>
  
Tags: <intelligent-agent><goal-based-agents><utility-based-agents><dijkstras-algorithm><prims-algorithm>
Title: What types of AI agents are Djikstra's algorithm and Prim's Minimum Spanning Tree algorithm?
UserDisplayName: Muhammad Maqsoodur Rehman
ThreadText: # What types of AI agents are Djikstra's algorithm and Prim's Minimum Spanning Tree algorithm?
  
  (Asked by: username_0 on 2020-04-26)
  
  From the perspective of the type of AI Agents, I would like to discuss Prim's Minimum Spanning Tree algorithm and Dijkstra's Algorithm.
  
  Both are model-based agents and both are "greedy algorithms".
  
  Both have their memory to store the history of vertices and their path distance. Prim's is **more greedy** than Dijkstra's algorithm whereas Dijkstra's algorithm is **more efficient** than Prim's.
  
  Can we say that Dijkstra's algorithm is a utility-based agent, whereas Prim's is a goal-based agent, with the justification that Prim's is **more goal-oriented** as compared to finding the optimum (shortest) path?
  
  **Tags:** intelligent-agent, goal-based-agents, utility-based-agents, dijkstras-algorithm, prims-algorithm
  
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  ## 1 answers
  
  ### Answer by username_1 on 2020-04-27. Score: 1 | Accepted answer
  
  Why do you want to think of these algorithms as agents?
  
  An agent is an abstract and higher-level concept than the concept of an algorithm, which is just a set of instructions.
  
  You could have two agents, one that is supposed to find the minimum spanning tree and another that is supposed to find the shortest path between a source and goal nodes. In both cases, these two agents have a goal, so they are both goal-oriented agents, but the algorithms they use to reach the goal are irrelevant, as long as they have one or more goals. If you have an agent that performs optimally with respect to some metric, you may want to call that agent an optimal agent.
  
  A similar logic applies to utility-based agents.
  
  So, in short, algorithms are used by agents to act, but the algorithms themselves are not the agents (unless you want to have a philosophical debate or use different definitions of agents). See [this answer](https://ai.stackexchange.com/a/12995/2444) for more details about the definition of agents.
  
  
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