Category Artificial Intelligence Assignments

Interactive Pervasive Computing – TinyOS is an operating system for low-power wireless computing

1. An on-line retailer has recently bought a dozen Segways (personal motorised scooter-like devices) to help their staff move quickly about the warehouse when picking and packing items for each order. They want to track the Segways within the warehouse (e.g. to help optimise their use) and also warn the driver of imminent collisions with other Segways. Describe an RFID-based scheme for sensing the location of the Segways to within about 3 metres using no more than one RFID reader per Segway. The RFID readers have a range of about 50 cm. Your description should include:

(a) A clearly drawn diagram showing how each component of the technology is positioned or attached;
(b) How each component is used including the flow of information through the system to a central database and web-interface...

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Games And Artificial Intelligence – A-Star is one example of a path-finding algorithm

1. (a) A-Star is one example of a path-finding algorithm. Describe what is meant by a search heuristic, using the A-Star heuristic as an example.

(b) (i) Describe the operation of a simple best-first-search algorithm. Include in your description an outline of the algorithm’s search strategy, appropriate pseudo-code and one advantage and disadvantage of the method.

(ii) Describe the operation of Dijkstra’s algorithm. Provide appropriate pseudo-code. Include in your description an outline of the algorithm’s search strategy, appropriate pseudo-code and one advantage and disadvantage of the method.
(c) Outline a general improvement or potential solution for each of the following path-finding issues: In a real-time game, where updates take place every 30ms, the path-finding algorithm ...

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Games & AI – Discuss the role of decision-making within an AI engine

1. (a) In relation to game AI, describe what the complexity fallacy refers to.

(b) Q-learning function:
Q(s,a) = (1 – α) Q(s,a) + α (r + γ max(Q(s’,a’)))
The Q-learning function is provided above. Describe Q-learning and how Q-values are used, making reference to the Q learning function and how Alpha α and Gamma γ affect learning, describing what will happen when each of these values is set to 0 and 1 respectively. List the other factors that are accounted for in the equation.

(c) Discuss the role of decision-making within an AI engine. Describe why a decision-making component is needed, where it fits in an AI framework and the expected inputs to and outputs from such a component.

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