A computer program that uses AI planning techniques is now the world champion computer program in the game of Contract Bridge. As reported in The New York Times and The Washington Post, this program--a new version of Great Game Products' The classical approach used in AI programs for games of strategy is to do a game tree search using the well-known minimax formula (eq. 1) The minimax computation is basically a bruteforce search: If implemented as formulated here, it would examine every node in the game tree. In practical implementations of minimax game tree searching, a number of techniques are used to improve the efficiency of this computation: putting a bound on the depth of the search, using alpha-beta pruning, doing transposition-table lookup, and so on. However, even with enhancements such as these, minimax computations often involve examining huge numbers of nodes in the game tree. Because a Bridge hand is typically played in just a few minutes, there is not enough time for a game tree search to search enough of this tree to make good decisions.
Of course, when we talk about robots in the business process context, we need to forget the old clichés of R2-D2, Wall-E or the Terminator. Or even the real-life robots used in manufacturing. RPA is the automation of rules-based processes with software that requires zero (or minimum) human interaction and applies it to Enterprise Resource Planning systems (ERPs), workflows, email systems and databases. It's this ability to interface between different systems and process work that makes RPA particularly appealing. And if you add to this compelling economics, relative ease of implementation and quick payback then RPA is a turbo-powered game changer in the hands of a seasoned Finance Transformation leader.
MS: Chris, two of the hottest topics in business and finance automation at the moment are'Robots' and'Artificial Intelligence'. They're almost used interchangeably, but I understand they're not the same. Can you explain the difference? CA: 'Artificial Intelligence' is arguably a bit more attention-grabbing in the headlines! But fundamentally, Robotics in finance means cutting-edge automation; sophisticated software which can be programmed within boundaries to, for example, code an invoice, or to receive a sales order and process it, and then match the payment to the order when it comes in.
Already home to some of the world's most innovative artificial intelligence companies, the UK has a rich ecosystem of investors, employers, developers and clients. These data sets can then be processed to create algorithms to drive machine learning – enabling computers to interpret data, predict outcomes and deliver solutions autonomously. Businesses must gather the right data, format it and then interpret it intelligently before creating algorithms to drive service or product lines and deliver solutions. This shouldn't be a hindrance, however, as it's the utilisation of smart algorithms and big data that's key to advancing machine learning.
Not too long ago, robots were considered a possible but surreal feature of a distant future. But take stock for a moment and it's clear that artificial intelligence and machine learning has already pervaded our lives. From high-frequency trading in financial markets to customised playlists on Spotify, machines are able to receive, process and act upon data intelligently. Machine learning and artificial intelligence are at the forefront of drastic change, and the world's largest technology companies, from Google and Amazon to Dyson, are focussed on harnessing artificial intelligence to revolutionise business and consumer services. Recognising its sea-change capabilities, the British Government is also committed to advancing artificial intelligence, predicting it could add £654 billion to the UK economy by 2035.
Tom Throop knows a lot about computers and the game of bridge. Back in 1958, while working at a U.S. Navy lab in the District, he programmed a Univac computer to play the game. Later, he designed bridge software for Radio Shack, Apple and Commodore computers. Eventually, he founded a company in Bethesda called Great Game Products Inc. that focused on selling his Bridge Baron software. But when Throop, 64, wanted to make the Bridge Baron a better player -- it lacked the ability to develop a strategy at the beginning of a game -- he knew he'd have to get some outside help in the world of artificial intelligence.
Bridge Baron is a computer program that plays bridge. It won the 1997 world championship of computer bridge, the Baron Barclay World Bridge Computer Challenge, as reported in The New York Times and The Washington Post. The five-day competition, which was hosted by the American Contract Bridge League in July 1997, included five computer programs, from the US, Japan, and Germany. The Bridge Baron won every head-to-head match that it played against the other programs.
A computer program that uses AI planning techniques is now the world champion computer program in the game of Contract Bridge. As reported in The New York Times and The Washington Post, this program -- a new version of Great Game Products' BRIDGE BARON program -- won the Baron Barclay World Bridge Computer Challenge, an international competition hosted in July 1997 by the American Contract Bridge League. It is well known that the game tree search techniques used in computer programs for games such as Chess and Checkers work differently from how humans think about such games. This article gives an overview of the planning techniques that we have incorporated into the BRIDGE BARON and discusses what the program's victory signifies for research on AI planning and game playing.