Although I have finished reading the Luger book, I am working on the exercises for each chapter starting with chapter 2. The propositional and predicate calculus exercises are interesting. I completed all the exercises except for the unify function. Otherwise I have been very busy.
I recently acquired the book Experiments in Induction by Hunt, Marin, and Stone (1966). Basically, this book is an accumulation of effort in the Concept Learning using the program called Concept Learning System (CLS) from 1961 to 1965. The rational for acquiring this book is due to many authors referencing this book. In the book the authors focus on the subject of conceptual learning, which leads to three different areas - pattern recongition, data classification, and induction. The book covers a number of experiments and enumerates a list of potential applications. Although LISP was in its infancy, the programs listed are written in IPL and the last one CLS-9 was in Algol programming language.
In addition I found an online version at Questia website of Hunt's book (1962) Concept Learning: An Information Processing Problem. I was able to read the first eleven pages before the site informed me to join site. The subscription rate is $9.95 per month for one subject area or $19.95 for unlimited access. The subject of conceptual learning is ongoing effort back in the 1950s and 1960s since the cognitive and computer scientists alike were studying on how a person develops concepts, then implement into a computerize algorithm. This effort was a collaboration between Hunt and Hovland.
This activity was triggered because I am still reading Machine Learning: An Artificial Intelligence Approach edited by Michalski, Carbonell, and Mitchell (1983) with Chapter 3 reading the survey written by Dietterich and Michalski called A Comparative Review of Selected Methods for Learning from Examples.
Friday, October 10, 2008
Tuesday, September 16, 2008
What is Artificial Intelligence?
What is artificial intelligence (AI)? The phrase Artificial Intelligence was coined in 1956 at a workshop. It is the branch of computer science concerned with the study of automation of intelligent behavior (Luger and Stubblefield 1992). The first successful artificial intelligent robot was Shakey the Robot, invented at the SRI International's Artificial Intelligence Center in the early 1970s. As an hardware agent, Shakey the Robot could make plans based on the environment around it. The robot receives inputs or percepts and performs actions.
Russell and Norvig takes the concept of the hardware robot into the software realm - in other words, the software robot (or softbot) receives inputs and performs actions. This leads to the generalization of agents - whether, it is a human, robot, or softbot. This leads to the idea of rational agents, which is the combination of agent program running on architecture (also known as computer hardware). Therefore, the AI is the study of rational agents and the components that builds them (Russell and Norvig 1995).
As an engineer, my goal is to understand and implement algorithms and architecture associated with rational agents to various environments and problems. In other words, develop a tools set with a solid mathematical foundations as to implement solutions to complex problems. After understanding the single agent environments, then my next focus will be on Multiple Agent Systems in Distributive Artificial Intelligence environment.
Russell and Norvig takes the concept of the hardware robot into the software realm - in other words, the software robot (or softbot) receives inputs and performs actions. This leads to the generalization of agents - whether, it is a human, robot, or softbot. This leads to the idea of rational agents, which is the combination of agent program running on architecture (also known as computer hardware). Therefore, the AI is the study of rational agents and the components that builds them (Russell and Norvig 1995).
As an engineer, my goal is to understand and implement algorithms and architecture associated with rational agents to various environments and problems. In other words, develop a tools set with a solid mathematical foundations as to implement solutions to complex problems. After understanding the single agent environments, then my next focus will be on Multiple Agent Systems in Distributive Artificial Intelligence environment.
Monday, September 15, 2008
AIMA Book
I have obtained a copy of the Artificial Intelligence: A Modern Approach (first ed) by Russell and Norvig (1995). Their approach is the study and design of agents (whether its a human, robot, or software agent) by unifying all AI topics - knowledge representation, natural langange, automated reasoning, planning, and machine learning. The book has 27 chapters and is divided into sections with the following names:
- Artificial Intelligence
- Problem-solving
- Knowledge and reasoning
- Acting logically
- Uncertain knowledge and reasoning
- Learning
- Communicating, perceiving, and acting
- Conclusions
Yes, I will encounter familiar topics and algorithms from my previous studies.
Friday, September 12, 2008
ML Algorithms
I am reviewing Chapter 12 of the Luger book and placing the pseudo code in my AI Notebook. So far I have copied the Version Space and ID3 Tree Induction algorithms. Dr. Luger has the Version space written in Prolog, but he has the ID3 algorithm written in CLOS. I also have a version of the ID3 tree induction algorithm written in LISP from Dr. Tom Mitchell. I already tested the LISP versions of ID3 algorithms. Also, pseudo code is provided for Explanation Based Learning, and Luger provides an example of EBL in Prolog. Finally the COBWEB algorithm is supplied in the unsupervised learning section, but no sample code is provided for in the text.
Friday, September 05, 2008
The journey continues
As I continue my AI journey, I discovered that I need to review my knowledge of probability theory and statistics. For example, I had to look up Bayes Theorem in Wikipedia, then in my college probability and statistics for engineers book. It has been a long while since I looked at probability and statistics. However, articles and works by Dr. Nils Nilsson uses probability theory and statistics and apply it to uncertainty.
Another area of interest has been the Bayesian Network (or Belief Network). There was an article in which a Bayesian Network illustrate probabilities in the leaves of trees. It is the uncertainty factor once again, but at this point I do not understand how it works, but I will sometime soon.
The last research item was the Support Vector Machine, which is a linear classification method. This method uses hyperplanes in geometric hyper space to determine the maximum distance to the hyperplane and data as to determine the maximum linear classification for the data. The current research uses nonlinear regression techniques and kernel methods to determine maximum data classification.
I am still continuing my studies in LISP programming. Like any other programming language that I have studied, you need to understand the basics and apply standard software engineering methods into the work. However, upon researching the job market, the only jobs are with research institutions or in the UK. Even with the newsgroup comp.lang.lisp, the recommendation is for an individual to focus their energy into java, html, java scripting, sql, etc.
Another area of interest has been the Bayesian Network (or Belief Network). There was an article in which a Bayesian Network illustrate probabilities in the leaves of trees. It is the uncertainty factor once again, but at this point I do not understand how it works, but I will sometime soon.
The last research item was the Support Vector Machine, which is a linear classification method. This method uses hyperplanes in geometric hyper space to determine the maximum distance to the hyperplane and data as to determine the maximum linear classification for the data. The current research uses nonlinear regression techniques and kernel methods to determine maximum data classification.
I am still continuing my studies in LISP programming. Like any other programming language that I have studied, you need to understand the basics and apply standard software engineering methods into the work. However, upon researching the job market, the only jobs are with research institutions or in the UK. Even with the newsgroup comp.lang.lisp, the recommendation is for an individual to focus their energy into java, html, java scripting, sql, etc.
Friday, August 29, 2008
Artificial Intelligence, Employment, and Income
Nearly a quarter century ago Dr. Nilsson (Nilsson 1984) wrote a report discussing the advantages of AI based robots taking over human toils. He discusses the benefits of such a system, and that human prosperity will be based on the income potential of robots owned by people. But also, there would be an increase in unemployment. In other words, people would not be working and need to start taking advantage of leisure. As result of this new labor model, humans would be free from daily toils of life and to return to paradise - a reference to Adam and Eve, whom were expelled from Paradise due to their shame for eating the forbidden fruit and gaining knowledge of the world.
However, the biggest change in the past quarter century was not AI robots but the personal computer introduced by IBM as a business solution. The PC has changed the way of business - information has been the key for business and workers in the world today. Today's children are well versed in the use of the PC and its associated technologies. Although the PC has improved the life of many workers, the workers still toil more than ever due to increases of productivity from the PC. The prosperity of business and workers depend on increasing productivity due to this technology.
By analogy, if AI robots became a tool for removing human toil, the workers would not be replaced and be unemployed. In fact, the worker would benefit and gain productivity. Should the AI robot appear, then my productivity would increase, and I would directly gained from my increased effort and toil. However, I would not gain any income or capital from AI robots. The corporations and the wealthy individuals would be the beneficiaries of such of a technology. I think that Dr. Nilsson was not on target with his assessment of middle class individuals gaining economic benefits of AI robot work force.
From history we must learn that high unemployment leads to political unstability and revolution. This was case between World War I and World War II, in which high unemployment lead to the rise of the Fasict parties in both Germany and Italy as well as expansion of Japanese Imperialism. The key to any stable political system is stable employment of its citizens. As for Dr. Nilsson's robot slave force, should these robots become self aware, they would initiate a war against mankind as explored in science fiction such as Battlestar Galatica.
In conclusion, Dr. Nilsson's new economy based on AI robot technology would not change the business model - in fact, the workers will still toil along with their robot counterparts with increased productivity for the benefit of the corporation's stock holders. Returning to paradise would not be possible.
References
Nilsson, N. 1984. Artificial Intelligence, Employment, and Income. Technical Note 322. SRI International, Menlo Park.
However, the biggest change in the past quarter century was not AI robots but the personal computer introduced by IBM as a business solution. The PC has changed the way of business - information has been the key for business and workers in the world today. Today's children are well versed in the use of the PC and its associated technologies. Although the PC has improved the life of many workers, the workers still toil more than ever due to increases of productivity from the PC. The prosperity of business and workers depend on increasing productivity due to this technology.
By analogy, if AI robots became a tool for removing human toil, the workers would not be replaced and be unemployed. In fact, the worker would benefit and gain productivity. Should the AI robot appear, then my productivity would increase, and I would directly gained from my increased effort and toil. However, I would not gain any income or capital from AI robots. The corporations and the wealthy individuals would be the beneficiaries of such of a technology. I think that Dr. Nilsson was not on target with his assessment of middle class individuals gaining economic benefits of AI robot work force.
From history we must learn that high unemployment leads to political unstability and revolution. This was case between World War I and World War II, in which high unemployment lead to the rise of the Fasict parties in both Germany and Italy as well as expansion of Japanese Imperialism. The key to any stable political system is stable employment of its citizens. As for Dr. Nilsson's robot slave force, should these robots become self aware, they would initiate a war against mankind as explored in science fiction such as Battlestar Galatica.
In conclusion, Dr. Nilsson's new economy based on AI robot technology would not change the business model - in fact, the workers will still toil along with their robot counterparts with increased productivity for the benefit of the corporation's stock holders. Returning to paradise would not be possible.
References
Nilsson, N. 1984. Artificial Intelligence, Employment, and Income. Technical Note 322. SRI International, Menlo Park.
Sunday, August 24, 2008
Progress Report
I have completed my review of Artificial Intelligence: Structures and Strategies for Complex Problem Solving (2nd ed) by George Luger and William Stubblefield. I ran some of the example LISP based programs such as the Logic Shell and the Expert System Shell from Chapter 14. For each program I had to write a LISP program to load the individual programs and start the shell.
To continue my studies in machine learning, I have a draft copy of Introduction to Machine Learning by Professor Nils J. Nilsson. Professor Nilsson's material contains a heavy dose of mathematics. I have not looked at partial dervivatives and probablity theory since my university courses in Partial differenital equations and Statistics and Probablity. After the heavy math, Professor Nilsson discusses Neural Networks with a strong emphasis in error correcting. Then later topics such as decision trees and inductive logic programming, Professor Nilsson finds similarities to Neural Nets with these topics. I basically perused the topics yesterday and today.
Then I signed onto Amazon and compared Dr. Nilsson's book with Dr. Mitchell's book on Machine Learning. From a topics point of view, both books are very similar.
Afterwards, going to Google and searching for Dr. Nilsson, I found his website and learned that he worked for Stanford Research Institute (known as SRI International today) in the AI Research Lab, and he graduated with his Ph.D. from Stanford University in 1959. In 1980, Dr. Nilsson and Kurt Konolige wrote a paper on Mulitple-Agent Planning Systems, one earliest papers on multi-agents on DAI pubished in the AAAI-80 Proceedings (pp 138-142).
To continue my studies in machine learning, I have a draft copy of Introduction to Machine Learning by Professor Nils J. Nilsson. Professor Nilsson's material contains a heavy dose of mathematics. I have not looked at partial dervivatives and probablity theory since my university courses in Partial differenital equations and Statistics and Probablity. After the heavy math, Professor Nilsson discusses Neural Networks with a strong emphasis in error correcting. Then later topics such as decision trees and inductive logic programming, Professor Nilsson finds similarities to Neural Nets with these topics. I basically perused the topics yesterday and today.
Then I signed onto Amazon and compared Dr. Nilsson's book with Dr. Mitchell's book on Machine Learning. From a topics point of view, both books are very similar.
Afterwards, going to Google and searching for Dr. Nilsson, I found his website and learned that he worked for Stanford Research Institute (known as SRI International today) in the AI Research Lab, and he graduated with his Ph.D. from Stanford University in 1959. In 1980, Dr. Nilsson and Kurt Konolige wrote a paper on Mulitple-Agent Planning Systems, one earliest papers on multi-agents on DAI pubished in the AAAI-80 Proceedings (pp 138-142).
Subscribe to:
Posts (Atom)
