IT’S ONLY CHECKERS, BUT THE COMPUTER TAUGHT ITSELF

July 28, 2000

FEATURES & COMMENTARY

New York, N.Y. — James Glanz reports that ever since an I.B.M. computer defeated Garry Kasparov, the world chess champion, in 1997, much of the suspense has gone out of the old battle of man versus machine: the machine won. But the lessons of a much humbler game have again made that battle fascinating. The game is, of all things, checkers.

Two computer scientists have leveled the playing field by asking a computer program called a neural network to do something much more difficult than beat a defenseless human at checkers. Knowing only the rules of checkers and a few basics, and otherwise starting from scratch, the program must teach itself how to play a good game without help from the outside world – including from the programmers.

The program did just that, using the electronic equivalent of natural selection. A sort of colony of the programs, each slightly different from all the others, played checkers against one another – quite ineptly at first – and chronic losers were killed off. Slightly mutated versions of the winners were allowed to reproduce. After hundreds of generations, blind evolution produced an expert checkers player, but not an infallible one.

The work was described last week in San Diego at the 2000 Congress on Evolutionary Computation by Dr. David B. Fogel, a computer scientist at Natural Selection Inc., a San Diego company.

The importance of the work, which Dr. Fogel did with Kumar Chellapilla, a doctoral student in electrical engineering at the University of California at San Diego, goes well beyond checkers to a question that has dogged computer science for decades: Can computers be designed to solve problems under circumstances that their human programmers never envisioned?

The question is relevant for circumstances as varied as an interstellar probe that loses contact with Earth and must adapt to unforeseen problems, or an automated factory scheduler attempting to deal with unexpected shortages or breakdowns.

All this from a good, but not perfect, game of checkers.

“The point here is that it learns to play by itself,” said Dr. Christopher Welty, a professor of computer science at Vassar College.

Because any particular version of Deep Blue, the I.B.M. program that defeated Mr. Kasparov, was based on strict rules and specific strategies given to it by humans, Dr. Welty said, “the way it played chess was very predictable – given the exact same game, it would play the same way twice.” But Dr. Fogel’s program can adapt without intervention by humans, he said.

The program made short work of two dozen casual players at last week’s conference, winning 25 timed “challenge matches,” losing none, and battling one player to a draw.

Whether Dr. Fogel’s best checkers program can improve beyond its current skill level is uncertain; it can hold its own with expert-rated players in official rankings but is generally blown off the board by players in the higher echelons of master and grand master players. The question of just how far such an adaptive algorithm can progress is a matter of intense debate among computer scientists, Dr. Welty said.

But Dr. Ali Zalzala, a computer scientist at Heriot-Watt University in Edinburgh and the principal organizer of the conference, said that just by taking on such questions, Dr. Fogel’s work may be shedding light on much deeper issues. Dr. Zalzala called the research “a very serious attempt to understand the operation of biological evolution.”

The neural networks that Dr. Fogel has bred into checkers players exist as software programs on his personal computer. To understand them, however, it helps to visualize the physical structures that the software is modeling. Those structures consist of a rather crude representation of the interconnected networks of neurons in the brain.

Living neurons are sometimes called “integrate-and-fire” structures. A neuron somehow integrates, or adds up, all the electrical stimuli it receives from other neurons that are connected to its receptors. If the sum rises above a certain threshold, it fires off its own electrical pulse, stimulating yet another set of neurons that behave in the same way.

The threshold for firing can be different for each neuron; so can its own firing intensity compared to the amount of input stimuli it receives, an amplification factor sometimes called the connection strength. At one end of the network might be sensory input from a pair of ears, for example, and at the other a conclusion like, “That is Bob’s voice.”

Any small part of the network might have connection strengths and thresholds to recognize one particular feature, like average pitch or the way a single vowel is pronounced. Because all parts of the network are interconnected, it can put all of these clues together almost simultaneously to draw a conclusion about whose voice is being heard.

Humans learn; no one is born able to recognize Bob’s voice. Likewise, the thresholds and connection strengths in Dr. Fogel’s network, which are geared toward recognizing sequences of moves in checkers rather than voices, can change as the program learns.

“As a human being, you are a pattern-recognizing device,” said Dr. Fogel, who added that his simple network could do the same thing.

But he did not give away the game by telling the network how. The network begins with 32 “sensory” inputs, one for each possible position on the board. Those inputs take on different values depending on whether a square is occupied by nothing, by an ordinary red or black piece, or by a king.

“Neurons” carrying those signals cross in a complex pattern of nested connections, reminiscent of a switchboard. Each neuron has a variable connection strength and each connection has a threshold. For a given configuration of checkers, the output of the network is a single number.

That number is in some way the network’s evaluation of the pattern on the board, a sort of output of pleasure or pain. At each point of the game, the computer evaluates it for the existing configuration and for possible ones it could create by making certain moves. Based on that information, it maximizes the number and makes moves, plays games.

Dr. Fogel began by creating several variants of his program, each with random connection strengths and thresholds. They played each other, and the regular losers – those for whom “pleasure” was not a reliable guide to playing a good game – were eliminated. The others, with random “mutations” that could allow better players to evolve, were given offspring. Eventually, he arrived at an expert player, a fact he verified by matching the program against ranked human players.

“The performance is remarkable,” said Dr. Michael Conrad, a professor of computer science at Wayne State University. “I’m still sort of surprised how good it is.”

Aside from getting beat by some humans, however, the program is not in the same league as Chinook, the computer checkers player devised in the early 1990’s by Dr. Jonathan Schaeffer of the University of Alberta in Canada. Chinook does not have a human equal at any level, Dr. Schaeffer said. But he said his program, like Big Blue, was infused with human expertise from the beginning rather than learning on its own.

How good Dr. Fogel’s program might someday become, and whether it could ever approach something like Chinook, is unknown. But Dr. Silvano Colombano, a computer scientist at the NASA Ames Research Center in California, said the same sort of evolutionary strategy could be built into computers aboard spacecraft that range too far from Earth to stay in contact.

“By analogy with the checkers game,” Dr. Colombano said, “the computer can play games with itself and become smarter.”

One thing such a spacecraft would have plenty of is time. In the long night of space, it might even decide to hone its checkers game.

============================================================

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Mira Supercomputer Enables Cancer Research Breakthrough

November 11, 2019

Dynamic partial-wave spectroscopic (PWS) microscopy allows researchers to observe intracellular structures as small as 20 nanometers – smaller than those visible by optical microscopes – in three dimensions at a mill Read more…

By Staff report

IBM Adds Support for Ion Trap Quantum Technology to Qiskit

November 11, 2019

After years of percolating in the shadow of quantum computing research based on superconducting semiconductors – think IBM, Rigetti, Google, and D-Wave (quantum annealing) – ion trap technology is edging into the QC Read more…

By John Russell

Tackling HPC’s Memory and I/O Bottlenecks with On-Node, Non-Volatile RAM

November 8, 2019

On-node, non-volatile memory (NVRAM) is a game-changing technology that can remove many I/O and memory bottlenecks and provide a key enabler for exascale. That’s the conclusion drawn by the scientists and researcher Read more…

By Jan Rowell

What’s New in HPC Research: Cosmic Magnetism, Cryptanalysis, Car Navigation & More

November 8, 2019

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

Machine Learning Fuels a Booming HPC Market

November 7, 2019

Enterprise infrastructure investments for training machine learning models have grown more than 50 percent annually over the past two years, and are expected to shortly surpass $10 billion, according to a new market fore Read more…

By George Leopold

AWS Solution Channel

Making High Performance Computing Affordable and Accessible for Small and Medium Businesses with HPC on AWS

High performance computing (HPC) brings a powerful set of tools to a broad range of industries, helping to drive innovation and boost revenue in finance, genomics, oil and gas extraction, and other fields. Read more…

IBM Accelerated Insights

Atom by Atom, Supercomputers Shed Light on Alloys

November 7, 2019

Alloys are at the heart of human civilization, but developing alloys in the Information Age is much different than it was in the Bronze Age. Trial-by-error smelting has given way to the use of high-performance computing Read more…

By Oliver Peckham

IBM Adds Support for Ion Trap Quantum Technology to Qiskit

November 11, 2019

After years of percolating in the shadow of quantum computing research based on superconducting semiconductors – think IBM, Rigetti, Google, and D-Wave (quant Read more…

By John Russell

Tackling HPC’s Memory and I/O Bottlenecks with On-Node, Non-Volatile RAM

November 8, 2019

On-node, non-volatile memory (NVRAM) is a game-changing technology that can remove many I/O and memory bottlenecks and provide a key enabler for exascale. Th Read more…

By Jan Rowell

MLPerf Releases First Inference Benchmark Results; Nvidia Touts its Showing

November 6, 2019

MLPerf.org, the young AI-benchmarking consortium, today issued the first round of results for its inference test suite. Among organizations with submissions wer Read more…

By John Russell

Azure Cloud First with AMD Epyc Rome Processors

November 6, 2019

At Ignite 2019 this week, Microsoft's Azure cloud team and AMD announced an expansion of their partnership that began in 2017 when Azure debuted Epyc-backed ins Read more…

By Tiffany Trader

Nvidia Launches Credit Card-Sized 21 TOPS Jetson System for Edge Devices

November 6, 2019

Nvidia has launched a new addition to its Jetson product line: a credit card-sized (70x45mm) form factor delivering up to 21 trillion operations/second (TOPS) o Read more…

By Doug Black

In Memoriam: Steve Tuecke, Globus Co-founder

November 4, 2019

HPCwire is deeply saddened to report that Steve Tuecke, longtime scientist at Argonne National Lab and University of Chicago, has passed away at age 52. Tuecke Read more…

By Tiffany Trader

Spending Spree: Hyperscalers Bought $57B of IT in 2018, $10B+ by Google – But Is Cloud on Horizon?

October 31, 2019

Hyperscalers are the masters of the IT universe, gravitational centers of increasing pull in the emerging age of data-driven compute and AI.  In the high-stake Read more…

By Doug Black

Cray Debuts ClusterStor E1000 Finishing Remake of Portfolio for ‘Exascale Era’

October 30, 2019

Cray, now owned by HPE, today introduced the ClusterStor E1000 storage platform, which leverages Cray software and mixes hard disk drives (HDD) and flash memory Read more…

By John Russell

Supercomputer-Powered AI Tackles a Key Fusion Energy Challenge

August 7, 2019

Fusion energy is the Holy Grail of the energy world: low-radioactivity, low-waste, zero-carbon, high-output nuclear power that can run on hydrogen or lithium. T Read more…

By Oliver Peckham

Using AI to Solve One of the Most Prevailing Problems in CFD

October 17, 2019

How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…

By James Sharpe

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce Read more…

By Tiffany Trader

D-Wave’s Path to 5000 Qubits; Google’s Quantum Supremacy Claim

September 24, 2019

On the heels of IBM’s quantum news last week come two more quantum items. D-Wave Systems today announced the name of its forthcoming 5000-qubit system, Advantage (yes the name choice isn’t serendipity), at its user conference being held this week in Newport, RI. Read more…

By John Russell

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Crystal Ball Gazing: IBM’s Vision for the Future of Computing

October 14, 2019

Dario Gil, IBM’s relatively new director of research, painted a intriguing portrait of the future of computing along with a rough idea of how IBM thinks we’ Read more…

By John Russell

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

Intel Confirms Retreat on Omni-Path

August 1, 2019

Intel Corp.’s plans to make a big splash in the network fabric market for linking HPC and other workloads has apparently belly-flopped. The chipmaker confirmed to us the outlines of an earlier report by the website CRN that it has jettisoned plans for a second-generation version of its Omni-Path interconnect... Read more…

By Staff report

Kubernetes, Containers and HPC

September 19, 2019

Software containers and Kubernetes are important tools for building, deploying, running and managing modern enterprise applications at scale and delivering enterprise software faster and more reliably to the end user — while using resources more efficiently and reducing costs. Read more…

By Daniel Gruber, Burak Yenier and Wolfgang Gentzsch, UberCloud

Dell Ramps Up HPC Testing of AMD Rome Processors

October 21, 2019

Dell Technologies is wading deeper into the AMD-based systems market with a growing evaluation program for the latest Epyc (Rome) microprocessors from AMD. In a Read more…

By John Russell

Intel Debuts Pohoiki Beach, Its 8M Neuron Neuromorphic Development System

July 17, 2019

Neuromorphic computing has received less fanfare of late than quantum computing whose mystery has captured public attention and which seems to have generated mo Read more…

By John Russell

Rise of NIH’s Biowulf Mirrors the Rise of Computational Biology

July 29, 2019

The story of NIH’s supercomputer Biowulf is fascinating, important, and in many ways representative of the transformation of life sciences and biomedical res Read more…

By John Russell

Xilinx vs. Intel: FPGA Market Leaders Launch Server Accelerator Cards

August 6, 2019

The two FPGA market leaders, Intel and Xilinx, both announced new accelerator cards this week designed to handle specialized, compute-intensive workloads and un Read more…

By Doug Black

With the Help of HPC, Astronomers Prepare to Deflect a Real Asteroid

September 26, 2019

For years, NASA has been running simulations of asteroid impacts to understand the risks (and likelihoods) of asteroids colliding with Earth. Now, NASA and the European Space Agency (ESA) are preparing for the next, crucial step in planetary defense against asteroid impacts: physically deflecting a real asteroid. Read more…

By Oliver Peckham

When Dense Matrix Representations Beat Sparse

September 9, 2019

In our world filled with unintended consequences, it turns out that saving memory space to help deal with GPU limitations, knowing it introduces performance pen Read more…

By James Reinders

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This