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You searched for +publisher:"Utah State University" +contributor:("Daniel Bryce"). Showing records 1 – 2 of 2 total matches.

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Utah State University

1. Robertson, Jared William. Planning in Incomplete Domains.

Degree: MS, Computer Science, 2012, Utah State University

Automated planning in computer science consists of finding a sequence of actions leading from an initial state to a goal state. People who have expert knowledge of the specific problem domain work with experts in automated planning to define the domain states and actions. This knowledge engineering required to create complete and correct domain descriptions for planning problems is often very costly and difficult. Our goal with incomplete planning is to allow people to program domains without the need for planning experts. Throughout the process of instruction of intelligent systems, teachers can often leave out whole procedures and aspects of action descriptions. In such cases, the alternative to making domains complete is to plan around the incompleteness. That is, given knowledge of the possible action descriptions, we seek out plans that will succeed despite any incompleteness in the domain formulation. A state in a domain consists of a set of propositions that can be either true or false. Actions in a domain require specific propositions to be true for the action to occur. Actions then add and remove propositions from the state to create a subsequent state. A valid plan consists of a sequence of actions that, starting with the initial state, change to match the goal state. An incomplete domain contains the same qualities as a complete domain, with the additional abilities of actions to possibly require a proposition to be true to initiate the action, as well as possibly adding and possibly removing propositions in the subsequent state. Actions that have possible preconditions and effects are referred to as incomplete actions. Because no prior work exists for the purpose of empirical comparisons, we compare our incomplete action planner, which we call DeFAULT, with a traditional planner that assumes all good possibilities and no bad possibilities will occur. DeFAULT finds much better quality plans than the traditional planner while maintaining similar speed. Advisors/Committee Members: Daniel Bryce, ;.

Subjects/Keywords: domain state; automated planning; set proposition; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Robertson, J. W. (2012). Planning in Incomplete Domains. (Masters Thesis). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/1435

Chicago Manual of Style (16th Edition):

Robertson, Jared William. “Planning in Incomplete Domains.” 2012. Masters Thesis, Utah State University. Accessed July 23, 2019. https://digitalcommons.usu.edu/etd/1435.

MLA Handbook (7th Edition):

Robertson, Jared William. “Planning in Incomplete Domains.” 2012. Web. 23 Jul 2019.

Vancouver:

Robertson JW. Planning in Incomplete Domains. [Internet] [Masters thesis]. Utah State University; 2012. [cited 2019 Jul 23]. Available from: https://digitalcommons.usu.edu/etd/1435.

Council of Science Editors:

Robertson JW. Planning in Incomplete Domains. [Masters Thesis]. Utah State University; 2012. Available from: https://digitalcommons.usu.edu/etd/1435


Utah State University

2. Redd, Justin R. The Effects of Abstraction on Best NBlock First Search.

Degree: MCS, Computer Science, 2013, Utah State University

Search is an important aspect of Artificial Intelligence and many advances have been achieved in finding optimal solutions for a variety of search problems. Up until recently most search problems were solved using a serial-single threaded approach. Speed is extremely important and one way to decrease the amount of time needed to find a solution is to use better hardware. A single threaded approach is limited in this way because newer processors are not much faster than previous generations. Instead industry has added more cores to allow more threads to work at the same time. In order to solve this limitation and take advantage of newer multi-core processors, many parallel approaches have been developed. The best approach to parallel search is an algorithm named Parallel Best-N Block First Search (PBNF). PBNF relies on an abstraction function to divide up the work in a way that allows threads to work efficiently with little contention. This thesis studies the way this abstraction function chooses to build the abstraction and demonstrates that better abstractions can be built. This abstraction focuses on goal variables on ways to keep the number of abstract states as small as possible while adding as many variables as feasible. Advisors/Committee Members: Daniel Bryce, ;.

Subjects/Keywords: abstraction; nblock; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Redd, J. R. (2013). The Effects of Abstraction on Best NBlock First Search. (Thesis). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/1476

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Redd, Justin R. “The Effects of Abstraction on Best NBlock First Search.” 2013. Thesis, Utah State University. Accessed July 23, 2019. https://digitalcommons.usu.edu/etd/1476.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Redd, Justin R. “The Effects of Abstraction on Best NBlock First Search.” 2013. Web. 23 Jul 2019.

Vancouver:

Redd JR. The Effects of Abstraction on Best NBlock First Search. [Internet] [Thesis]. Utah State University; 2013. [cited 2019 Jul 23]. Available from: https://digitalcommons.usu.edu/etd/1476.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Redd JR. The Effects of Abstraction on Best NBlock First Search. [Thesis]. Utah State University; 2013. Available from: https://digitalcommons.usu.edu/etd/1476

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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