Artificial Intelligence: DNA sequencers to dancing robots
Published: 28 Mar 2006 11:40 BST
... extensively used in the machine-learning capabilities of both Amazon and Google, and have proved an efficient way for a spam filter to learn the characteristics of spam by analysing previous accepted and rejected messages. However, not all Bayesian systems are appreciated: the much-despised Microsoft Office paper-clip assistant was also based upon a Bayesian inference system.
A good example of the way that the learning capability of Bayesian networks are being used is to be found in their use by an increasing number of computer game designers. They allow the game to dynamically learn from the human player and thus be better able to anticipate his or her moves. For example the Drivatars from Forza Motorsport that have been developed by Microsoft for this Xbox racing program include a sophisticated AI capable of probabilistic racing-line generation. This software is not only used to learn from the players driving techniques and react to them but it can also be used to create the racing line for all the computer generated vehicles by learning from the actions of a real human driver on a real course.
Intelligent agents
Intelligent agents are another form of artificial intelligence software that has now found a wide range of applications. An intelligent agent is a goal-directed, autonomous, persistent and intelligent piece of code that is designed to perform a specific function. Agents can be used to monitor real time events or search through databases, and when provided with communications capability multiple agents can be used to solve many inherently complex problems.
One area where intelligent agents are being employed in deadly earnest is in financial markets. Here algorithmic trading systems, as such agents are known, are being routinely used to decide exactly when to buy or sell shares or commodities. These agents allow investment managers to buy or sell large holdings without moving the market, they do this by sharing the buying or selling task between a large number of agents each of which has the power to monitor the market and decide exactly when to buy or sell.
According to Richard Balarkas of Credit Suisse First Boston "agents are very sophisticated [and] are doing what a trader would like to do". Whereas a human trader may only look at three or four variables before buying or selling, an agent may look at hundreds.
These agents not only relieve financial traders of a routine task, but they are also capable of doing it much better. In 2001 IBM conducted a trial of trading agents and this demonstrated that when pitched against each other the intelligent agents did better than their human counterparts and made on average 7 percent more cash.
Desert challenge.
Back in 2004 the US Defense Advanced Research Projects Agency, DARPA, issued a challenge to AI researchers to create an autonomous vehicle that could take part in a 212km race against other similar vehicles on a course that ran through some extremely rough desert terrain. The prize for the team whose vehicle completed the race in the shortest time was $2m.
On 8 October 2005, 23 robot vehicles took part in the race which took them on a dirt road course along narrow mountain tracks and through tunnels to a finishing line outside Primm, Nevada. Five of the vehicles completed the course, with the winner, a converted Volkswagen Touareg R5 SUV entered by the artificial intelligence lab at Stanford University California, taking just 6 hours and 53 minutes.
The winning vehicle was fitted with a range of sensors, including video cameras, radar, accelerometers, laser range finders and a GPS system, along with six computers and some very advanced AI software. The vehicle's software had been trained by being driven over 2000km of desert track during which time the sensors observed the terrain through which the vehicle was driven and what actions the human driver took to stay on course.
The DARPA challenge was prompted by plans to use AI and autonomous vehicle technology both in the next generation of military vehicles, and in a new generation of planetary rovers. However, the technology demonstrated in this challenge may also result in the near future in AI systems being used to improve vehicle safety.
A matter of common sense
Marvin Minsky co-founder of the world famous MIT Artificial Intelligence Laboratory declared in a recent speech at Boston University that "AI has been brain-dead since the 1970s." He was referring to the fact that researchers have since then been primarily concerning themselves with small facets of the machine intelligence problem as opposed to looking at the task as a whole.
Throughout the 1980s researchers developed expert systems that emulated human expertise in tightly defined areas like law and medicine, and in such areas...
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