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--- coursework:2014f:moshe_sipper [2014/10/29 17:47] – [Games] lnunno
+++ coursework:2014f:moshe_sipper [2014/11/03 20:00] (current) – lnunno
@@ Line 12: / Line 12: @@
 Dr. Sipper has published over 160 scientific publications including three research-related books: Evolved to Win, Machine Nature: The Coming Age of Bio-Inspired Computing, and Evolution of Parallel Cellular Machines: The Cellular Programming Approach.
-Dr. Sipper won the 2015 IEEE CIS Outstanding TCIAIG Paper award, the 2008 BGU Toronto Prize for Academic Excellence in Research, the 1999 EPFL Latsis Prize, and six HUMIE Awards — Human-Competitive Results Produced by Genetic and Evolutionary Computation (Gold, 2013; Gold, 2011; Bronze, 2009; Bronze, 2008; Silver, 2007; Bronze, 2005).
+Dr. Sipper won the 2015 IEEE CIS Outstanding Transactions on Computational Intelligence and AI in Games (TCIAIG) Paper award, the 2008 BGU Toronto Prize for Academic Excellence in Research, the 1999 EPFL Latsis Prize, and six HUMIE Awards — Human-Competitive Results Produced by Genetic and Evolutionary Computation (Gold, 2013; Gold, 2011; Bronze, 2009; Bronze, 2008; Silver, 2007; Bronze, 2005).
+{{ :coursework:2014f:hclogomf.jpg?300 |}}
 As you can see, he's a very busy guy...
@@ Line 20: / Line 22: @@
 ===== Work in Evolutionary Computation =====
 Dr. Sipper is interested in using evolutionary algorithms to software development and games. In his book [[http://www.lulu.com/shop/moshe-sipper/evolved-to-win/ebook/product-18719826.html|Evolved to Win (free download)]] he details how he has created programs that do well in a variety of games including: Chess, FreeCell, Backgammon, Checkers, and Reversi to name a few.
+==== Evolution of Parallel Cellular Machines ====
+Sipper's most cited work (according to Google Scholar) is his 1997 book [[ftp://212.235.189.206/PST_books/EvolutionOfParallelCellularMachines_MosheSipper.pdf|Evolution of Parallel Cellular Machines: The Cellular Programming Approach]].
+  * Asks: "can we mimic nature's achievements of parallel cellular machines?"
+  * Shows universal computation can be attained in cellular spaces.
+      * Explains how logic gates, wires, signals, clock, and memory can all be embedded in CAs. In chapter 2 of the book, a pretty interesting read.
+  * Explores the coevolution of cellular computation.
+  * Shows the Firefly machine which is an online autonomous "evolware"
+{{ :coursework:2014f:firefly.png |}}
 ==== Darwinian Software Engineering ====
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   * Has been used to solve the Artificial Ant and Intwined Spirals problem.
   * Prides itself on turning bad seeds into good programs. But how bad can they really be?
-  * Fixed a good Tic-Tac-Toe solver that had a couple of subtle bugs.
+  * Fixed a "good" Tic-Tac-Toe solver that had a couple of subtle bugs.
 ==== Games ====
 Dr. Sipper has been active in applying evolutionary computation to games since 2005. It appears that this is his true passion. He has 25 publications (his most in a particular field) in the area of games and it is featured heavily on his personal site.
+He uses a combination of genetic algorithms with heuristics to build programs that are capable of competing against humans in a variety of games.
+His research group has developed a custom [[http://en.wikipedia.org/wiki/IDA*| IDA*]] algorithm which utilizes heuristics to search the solution space of games. Much of the research done by Sipper takes the form of developing heuristics for common games and implementing genetic algorithms to mutate these heuristics.
+Sipper takes pride in creating GP players that beat other top algorithms and players. Some of his achievements in games include:
+  * Has the #1 FreeCell solver on freecell.net
+  * Evolved a mate-in-n Chess engine that beats the "Crafty" chess engine.
+  * Evolved a Backgammon player that is "able to beat all previous machine learning-created players."
 === Rush Hour ===
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 {{:coursework:2014f:rush-hour-start.png?200|}} {{:coursework:2014f:rush-hour-end.png?200|}}
+{{ :coursework:2014f:rh-methods.png?600 |}}
+Some of the heuristics include:
+  * Goal distance.
+  * Number of cars blocking the goal.
+  * How many cars are freed by a given move.
+  * How difficult the problem is.
+  * If a move places a car where no other cars can reach.
+The genetic algorithm evolves //when// to apply a certain heuristic. The genome consists of a set of policies. Genetic algorithms were also used to evolve more difficult puzzles when the algorithm was able to solve 6x6 puzzles easily.
+{{ :coursework:2014f:rush_hour.png |}}
 ===== Work in Fiction =====
 Interestingly, Dr. Sipper is an author of three science fiction novels: Daniel Max and the King in the Tower, Xor: The Shape of Darkness, and The Peaceful Affair in addition to writing comics and regular short stories on his blog.
+It appears that his target audience is young adults and his writing style is light science fiction, not necessarily rooted in hard science with the presence of wolf-men and aliens from other worlds making a regular appearance.
 Xor: The Shape of Darkness is his most popular and well received book (according to Goodreads).
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   * [[http://sipperstories.blogspot.com/|Blog]]
   * [[https://www.goodreads.com/author/show/705059.Moshe_Sipper|Goodreads page]]
+  * [[http://scholar.google.com/citations?user=k2xM7QgAAAAJ&hl=en&oi=ao|Google Scholar Page]]