
By W. Teahan
ISBN-10: 8776815927
ISBN-13: 9788776815929
Read Online or Download Artificial Intelligence - Exercises - Agent Behaviour I [math] PDF
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Extra resources for Artificial Intelligence - Exercises - Agent Behaviour I [math]
Sample text
No-of-nodes: This is the number of nodes to place in the network. - no-of-super-nodes: This is the number of super-nodes to place in the network. (These are nodes that usually will have significantly more links than standard nodes as specified by links-per-super-node slider). - links-per-node: This specifies the maximum number of links a standard node will have. The actual number chosen for a particular node will be a random number between 1 and this number. 57 7. Communication Artificial Intelligence: Exercises – Agent Behaviour I - links-per-super-node: This specifies the maximum number of links a super-node will have.
59 7. Communication Artificial Intelligence: Exercises – Agent Behaviour I Notice that when there is a learning effect due to the knowledge sharing mechanism, the Successful Searches plot will start to curve upwards rather then continue as a straight line. Why is this? What settings and type of networks does this occur for? Can you get the curve to bend downwards instead of upwards? (Hint: Try changing the value of one or two of the sliders midstream). Notice how the effectiveness of the search deteriorates as the network changes when nodes are either added or deleted.
P2P-has-super-nodes": This simulates a peer-to-peer network with super-nodes. "P2P-random-single-link": This simulates a peer-to-peer network where each node has only one link with another random node. "P2P-incremental": This creates the simulated peer-to-peer network by incrementally building the links to other random nodes one at a time. "P2P-incremental-1": This creates the simulated peer-to-peer network by incrementally building links to other random nodes. e. the goal node) as the central hub and all other nodes linked to it and not to any other node.
Artificial Intelligence - Exercises - Agent Behaviour I [math] by W. Teahan
by Daniel
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