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Events for May 29, 2014
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SAP TERP 10 Student Certification AcademyThu, May 29, 2014
Executive Education
Conferences, Lectures, & Seminars
Speaker: TBD,
Talk Title: SAP TERP 10 Student Certification Academy
Abstract: Course Number & Dates: Session 1 (SAP 0514-05):
Monday, May 19th - Saturday May 24th, 2014
Tuesday, May 27th - Thursday, May 29th, 2014
Certification Exam on Friday, May 30th, 2014(10 day course includes one Saturday class on May 24th)
The University of Southern California, being an active member of SAPââ¬â¢s Global University Alliances program since its inception in 1996, has been chosen to offer the TERP10 Academy to its students in early Summer 2014. The TERP10 Academy, and its certification, is a direct response to the global forecast of needed SAP skills in the market, estimated between 30,000 and 40,000, in the next several years. Students completing the TERP10 Academy and passing SAPââ¬â¢s certification exam will have the advantage of being equipped with a good understanding of business processes adopted by companies around the world. They will also get insights into best business practices and how SAP can be used to optimize business processes. Students will find that the TERP10 Certification will open internship opportunities as well as full time jobs with consulting firms such as Deloitte, Ernst and Young, KPMG, Hitachi, and other SAP partner companies.
Host: Professional Programs
More Info: http://gapp.usc.edu/professional-programs/short-courses/terp10#overview
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
Event Link: http://gapp.usc.edu/professional-programs/short-courses/terp10#overview
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DEN@Viterbi Limited Status Online Information Session
Thu, May 29, 2014 @ 11:00 AM - 12:00 PM
DEN@Viterbi, Viterbi School of Engineering Graduate Admission, Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Limited Status allows qualified individuals to begin taking classes via DEN@Viterbi before being formally admitted to a degree program. The Viterbi School uses a state-of-the-art, proprietary Web-based delivery system that enables students from around the world to access classes live, on demand or by download. To find out if you are eligible for this enrollment offering and to see how you can begin taking classes this spring, join us for this online information session.
Click to RSVPAudiences: RSVP Required
Contact: Viterbi Professional Programs
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PhD Defense - Xiaoming Zheng
Thu, May 29, 2014 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
Thesis Title: Auction and Negotiation Algorithms for Decentralized Task Allocation
Date: May 29th, 2014
Time: 2:00 pm
Location: GFS 111
Committee: Prof. Sven Koenig (Chair)
Prof. Craig Tovey
Prof. David Kempe
Prof. Maged Dessouky (Outside Member)
Abstract:
It is often important to coordinate a team of robots
well in a distributed computing environment. In this dissertation, we study how to allocate and re-allocate tasks to distributed robots so that the team cost is as small as possible (= the team performance is as high as possible). Researchers have developed several algorithms based on auction-like and negotiation-like protocols for decentralized task allocation. However, the majority of these existing algorithms use either single-item auctions, in which only one task is allocated to some robot in one round so that the team cost increases the least, or single-item exchanges, in which only one task is transferred between two robots in one round so that the team cost decreases the most. These algorithms usually result in highly sub-optimal allocations and do not apply to complex tasks that need to be executed by more than one robot
simultaneously.
We develop a new auction algorithm, called sequential auctions
with bundles, that extends single-item auctions to be able to
allocate more than one task to robots in one round so that the team cost increases the least. We introduce a novel data structure, called bid trees, that each robot can construct and submit to the auctioneer independently. Theoretical results show that the bids from bid trees can succinctly characterize all necessary local information of robots needed by the auctioneer to allocate multiple tasks to robots in one round so that the team cost increases the least. Experimental results show that sequential auctions with bundles reduce the team costs of single-item auctions significantly.
We develop a new negotiation algorithm, called sequential
negotiations with K-swaps, that extends single-item exchanges to
be able to re-allocate more than one task among robots in one round so that the team cost decreases the most. We introduce a novel data structure, called partial k-swaps, that each robot can
construct and propose to other robots independently. Theoretical
results show that profitable partial k-swaps can succinctly
characterize all necessary local information of robots needed to
re-allocate multiple tasks among them so that the team cost
decreases the most. Experimental results show that sequential
negotiations with K-swaps reduce the team costs of given
initial allocations significantly.
We develop a new auction algorithm, called sequential auctions
with reaction functions, that extends single-item auctions to be
able to allocate either a simple or complex task to robots in one
round so that the team cost increases the least. We introduce a novel data structure, called reaction functions, that each robot can construct and submit to the auctioneer independently. Theoretical results show that reaction functions can succinctly characterize all necessary local information of robots needed by the auctioneer to allocate either a simple or complex task to robots in one round so that the team cost increases the least. Experimental results show that sequential auctions with reaction functions reduce the team costs of an existing auction algorithm significantly.
Finally, we develop a new negotiation algorithm, called sequential negotiations with reaction functions, that extends single-item exchanges to be able to re-allocate complex or simple tasks among robots in one round so that the team cost decreases the most. Theoretical results show that reaction functions can succinctly characterize all necessary local information of robots needed to re-allocate complex or simple tasks among them so that the team cost decreases the most. Experimental results show that sequential negotiations with reaction functions reduce the team costs of given initial allocations significantly.
To summarize, in this dissertation we develop new auction and
negotiation algorithms for solving task-allocation problems with
simple and complex tasks and demonstrate empirically that
these new algorithms reduce the team costs of existing ones
significantly.
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 111
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
