Re: Re: Peirce's concept of logical abduction-- a possible moneymaker
Hi Bruno Marchal My principal interest over the years has been to come up with some self-sustaining self-generating method of autopoeisis. That's why I found the I Ching fascinating. It contains sensible links between binary numbers and metaphors. When I look up methods of data mining, all they give is hierarchy diagrams and numbers. How do they link numbers and metaphors or words in general ? Perhaps there is some sort of bayesian scheme to do that. Roget's thesaurus might also be a starting point, since they have words of similar meanings clustered, but where you go from that beats me. Roger Clough, rclo...@verizon.net 11/8/2012 Forever is a long time, especially near the end. -Woody Allen - Receiving the following content - From: Bruno Marchal Receiver: everything-list Time: 2012-11-07, 12:57:14 Subject: Re: Peirce's concept of logical abduction-- a possible moneymaker On 07 Nov 2012, at 18:12, Roger Clough wrote: Hi Bruno Marchal Cool. Shows you how little I know. Those things are virtually unknown by most. Computer science is very technical, and the number of publications is explosive, almost an industry. It is also a gold mine, alas, most philosophy curriculum does not have good courses in the field. We separate the human and the exact sciences, which does not help. In science we still kill the diplomats, and this means that science is still run by unconscious (pseudo)-religion, if not simply the boss is right theory. Of course the degree of graveness is very variable in time and places. Bruno Roger Clough, rclo...@verizon.net 11/7/2012 Forever is a long time, especially near the end. -Woody Allen - Receiving the following content - From: Bruno Marchal Receiver: everything-list Time: 2012-11-07, 12:05:11 Subject: Re: Peirce's concept of logical abduction-- a possible moneymaker Hi Roger Clough, Hi Bruno Marchal Yes, by new I mean contingent. But Kant, although his examples are debatable, at least sought a synthetic a priori, which of course would be a gold mine, or perhaps a stairway to the divine. Pragmatism rejects the idea of there being any such universals, but I think by abduction strives to obtain completly new results (if actually new I can't say). I think that's why Peirce came up with the concept of abduction. The concept is very seductive to me for its possible power of discovery of something unknown or new. If comp could do this, I'd not spend a moment more on simulating the brain. Such a program might be worth a lot of money in venues such as AI, the defense industry, medicine and criminal investigation a la Sherlocki Holmes. Abduction is just one technic among many to do inductive inference (predicting theories from fact, synthesizing programs from input- output sequences, finding explanations from data, etc.). The mathematical theory of inductive inference is a very large subfield of theoretical computer science and theoretical artificial Intelligence, or Learning theory. AI is the practice and/or experimental part of it. Behavioral Comp is the idea that machines can emulate all 3p aspect of experience and consciousness. STRONG AI is the thesis that machine can have 1p experience. COMP is the thesis that *you* are emulable by a computer. Famous theorem in theoretical learning theory: Roughly speaking we measure the intelligence (really competence) by the largeness of the class of computable processes recognized (explained, inferred) by a machine, or by the number of such classes (or comobinations). What is *much* more clever than a machine? Answer: two machines. It is the non union theorem of Blum and Blum. Actually, and in general, the gap of intelligence is incomputably big. A machine which can change its mind n times is also incomputably more clever than a machine which changes its mind m times, if m n. (Case and Smith) A surprising result: a machine which is able to change its mind, despite he got a correct theory, is again *much more* clever than a machine which sticks on the correct theory! (Case and Smith). Case Al. refuted also a form of strict Popperianism. Machines able to infer irrefutable theories can learn larger classes, and more classes, of computable process. Most result are, as we could expect, non constructive. No machine can really construct a machine and prove that such machine is more clever than herself. But of course machine can do that serendipitously, and machine can build other hierarchies, close to form of biological self-extension. References below. Theoretical computer science is a *very* large part of mathematical logic. With both a deductive and an inference inductive part. Computer are very peculiar objects. They seem close to what you say about
Re: Peirce's concept of logical abduction-- a possible moneymaker
Hi Roger Clough , On 08 Nov 2012, at 11:03, Roger Clough wrote: Hi Bruno Marchal My principal interest over the years has been to come up with some self-sustaining self-generating method of autopoeisis. That's why I found the I Ching fascinating. It contains sensible links between binary numbers and metaphors. When I look up methods of data mining, all they give is hierarchy diagrams and numbers. How do they link numbers and metaphors or words in general ? Perhaps there is some sort of bayesian scheme to do that. Roget's thesaurus might also be a starting point, since they have words of similar meanings clustered, but where you go from that beats me. You should perhaps study how works a computer (or a universal number). They transforms numbers into words and actions all the time, and this in a non metaphorical way. And they can do much more, like referring to themselves in the 3p but also in the 1p and other senses. There is no more magic than in computer science, imo. Bruno Roger Clough, rclo...@verizon.net 11/8/2012 Forever is a long time, especially near the end. -Woody Allen - Receiving the following content - From: Bruno Marchal Receiver: everything-list Time: 2012-11-07, 12:57:14 Subject: Re: Peirce's concept of logical abduction-- a possible moneymaker On 07 Nov 2012, at 18:12, Roger Clough wrote: Hi Bruno Marchal Cool. Shows you how little I know. Those things are virtually unknown by most. Computer science is very technical, and the number of publications is explosive, almost an industry. It is also a gold mine, alas, most philosophy curriculum does not have good courses in the field. We separate the human and the exact sciences, which does not help. In science we still kill the diplomats, and this means that science is still run by unconscious (pseudo)-religion, if not simply the boss is right theory. Of course the degree of graveness is very variable in time and places. Bruno Roger Clough, rclo...@verizon.net 11/7/2012 Forever is a long time, especially near the end. -Woody Allen - Receiving the following content - From: Bruno Marchal Receiver: everything-list Time: 2012-11-07, 12:05:11 Subject: Re: Peirce's concept of logical abduction-- a possible moneymaker Hi Roger Clough, Hi Bruno Marchal Yes, by new I mean contingent. But Kant, although his examples are debatable, at least sought a synthetic a priori, which of course would be a gold mine, or perhaps a stairway to the divine. Pragmatism rejects the idea of there being any such universals, but I think by abduction strives to obtain completly new results (if actually new I can't say). I think that's why Peirce came up with the concept of abduction. The concept is very seductive to me for its possible power of discovery of something unknown or new. If comp could do this, I'd not spend a moment more on simulating the brain. Such a program might be worth a lot of money in venues such as AI, the defense industry, medicine and criminal investigation a la Sherlocki Holmes. Abduction is just one technic among many to do inductive inference (predicting theories from fact, synthesizing programs from input- output sequences, finding explanations from data, etc.). The mathematical theory of inductive inference is a very large subfield of theoretical computer science and theoretical artificial Intelligence, or Learning theory. AI is the practice and/or experimental part of it. Behavioral Comp is the idea that machines can emulate all 3p aspect of experience and consciousness. STRONG AI is the thesis that machine can have 1p experience. COMP is the thesis that *you* are emulable by a computer. Famous theorem in theoretical learning theory: Roughly speaking we measure the intelligence (really competence) by the largeness of the class of computable processes recognized (explained, inferred) by a machine, or by the number of such classes (or comobinations). What is *much* more clever than a machine? Answer: two machines. It is the non union theorem of Blum and Blum. Actually, and in general, the gap of intelligence is incomputably big. A machine which can change its mind n times is also incomputably more clever than a machine which changes its mind m times, if m n. (Case and Smith) A surprising result: a machine which is able to change its mind, despite he got a correct theory, is again *much more* clever than a machine which sticks on the correct theory! (Case and Smith). Case Al. refuted also a form of strict Popperianism. Machines able to infer irrefutable theories can learn larger classes, and more classes, of computable process. Most result are, as we could expect, non constructive. No machine can really construct a machine and prove that such machine is more clever than herself. But of course machine can do that serendipitously, and machine can build other hierarchies, close to form of biological self-extension. References below. Theoretical
Re: Peirce's concept of logical abduction-- a possible moneymaker
On 11/7/2012 10:13 AM, Roger Clough wrote: Hi Bruno Marchal Yes, by new I mean contingent. But Kant, although his examples are debatable, at least sought a synthetic a priori, which of course would be a gold mine, or perhaps a stairway to the divine. Pragmatism rejects the idea of there being any such universals, but I think by abduction strives to obtain completly new results (if actually new I can't say). I think that's why Peirce came up with the concept of abduction. The concept is very seductive to me for its possible power of discovery of something unknown or new. If comp could do this, I'd not spend a moment more on simulating the brain. Such a program might be worth a lot of money in venues such as AI, the defense industry, medicine and criminal investigation a la Sherlocki Holmes. http://en.wikipedia.org/wiki/Abductive_reasoning http://en.wikipedia.org/wiki/Abductive_reasoning%20 Abduction[1] is a form of logical inference that goes from data description of something to a hypothesis that accounts for the reliable data and seeks to explain relevant evidence. The term was first introduced by the American philosopher Charles Sanders Peirce (1839?1914) as guessing.[2] Peirce said that to abduce a hypothetical explanation from an observed surprising circumstance is to surmise that may be true because then would be a matter of course.[3] Thus, to abduce from involves determining that is sufficient (or nearly sufficient), but not necessary, for [b, unclear symbol]. For example, the lawn is wet. But if it rained last night, then it would be unsurprising that the lawn is wet. Therefore, by abductive reasoning, the possibility that it rained last night is reasonable. (But note that Peirce did not remain convinced that a single logical form covers all abduction.)[4] Peirce argues that good abductive reasoning from P to Q involves not simply a determination that, e.g., Q is sufficient for P, but also that Q is among the most economical explanations for P. Simplification and economy are what call for the 'leap' of abduction.[5] In abductive reasoning, unlike in deductive reasoning, the premises do not guarantee the conclusion. Abductive reasoning can be understood as inference to the best explanation.[6] There has been renewed interest in the subject of abduction in the fields of law,[7] computer science, and artificial intelligence research.[8] Dear Roger, I am a HUGE fan of Peirce. I hope to work with you and any one else to elaborate on his ideas. I think that there are no ideal absolutes except only those Hintikka decision games http://www.springerlink.com/content/k2727246n056x1lu/fulltext.pdfconverge to Nash equilibria http://en.wikipedia.org/wiki/Nash_equilibrium in some finite number of steps. -- Onward! Stephen -- You received this message because you are subscribed to the Google Groups Everything List group. To post to this group, send email to everything-list@googlegroups.com. To unsubscribe from this group, send email to everything-list+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/everything-list?hl=en.
Re: Peirce's concept of logical abduction-- a possible moneymaker
Hi Roger Clough, Hi Bruno Marchal Yes, by new I mean contingent. But Kant, although his examples are debatable, at least sought a synthetic a priori, which of course would be a gold mine, or perhaps a stairway to the divine. Pragmatism rejects the idea of there being any such universals, but I think by abduction strives to obtain completly new results (if actually new I can't say). I think that's why Peirce came up with the concept of abduction. The concept is very seductive to me for its possible power of discovery of something unknown or new. If comp could do this, I'd not spend a moment more on simulating the brain. Such a program might be worth a lot of money in venues such as AI, the defense industry, medicine and criminal investigation a la Sherlocki Holmes. Abduction is just one technic among many to do inductive inference (predicting theories from fact, synthesizing programs from input- output sequences, finding explanations from data, etc.). The mathematical theory of inductive inference is a very large subfield of theoretical computer science and theoretical artificial Intelligence, or Learning theory. AI is the practice and/or experimental part of it. Behavioral Comp is the idea that machines can emulate all 3p aspect of experience and consciousness. STRONG AI is the thesis that machine can have 1p experience. COMP is the thesis that *you* are emulable by a computer. Famous theorem in theoretical learning theory: Roughly speaking we measure the intelligence (really competence) by the largeness of the class of computable processes recognized (explained, inferred) by a machine, or by the number of such classes (or comobinations). What is *much* more clever than a machine? Answer: two machines. It is the non union theorem of Blum and Blum. Actually, and in general, the gap of intelligence is incomputably big. A machine which can change its mind n times is also incomputably more clever than a machine which changes its mind m times, if m n. (Case and Smith) A surprising result: a machine which is able to change its mind, despite he got a correct theory, is again *much more* clever than a machine which sticks on the correct theory! (Case and Smith). Case Al. refuted also a form of strict Popperianism. Machines able to infer irrefutable theories can learn larger classes, and more classes, of computable process. Most result are, as we could expect, non constructive. No machine can really construct a machine and prove that such machine is more clever than herself. But of course machine can do that serendipitously, and machine can build other hierarchies, close to form of biological self- extension. References below. Theoretical computer science is a *very* large part of mathematical logic. With both a deductive and an inference inductive part. Computer are very peculiar objects. They seem close to what you say about the supreme monads, but the supreme monads are not Gods, they are only God reflector, or God mirror. God is more like the whole truth, I mean the whole arithmetical truth, which contains the many truth concerning many universal numbers and universal relation between numbers. The monads are windows through which God can take a look at itself, but the supreme-monads the universal numbers, are window enough large so that God can begin to recognize itself, so to speak. Bruno BLUM L. BLUM M., 1975, Toward a Mathematical Theory of Inductive Inference. Information and Control 28,.pp. 125-155. CASE J. SMITH C., 1983, Comparison of Identification Criteria for Machine Inductive Inference. In Theoretical Computer Science 25,.pp 193-220. CASE J. NGO-MANGUELLE S., 1979, Refinements of inductive inference by Popperian machines. Tech. Rep., Dept. of Computer Science, State Univ. of New- York, Buffalo. http://en.wikipedia.org/wiki/Abductive_reasoning Abduction[1] is a form of logical inference that goes from data description of something to a hypothesis that accounts for the reliable data and seeks to explain relevant evidence. The term was first introduced by the American philosopher Charles Sanders Peirce (1839?1914) as guessing.[2] Peirce said that to abduce a hypothetical explanation from an observed surprising circumstance is to surmise that may be true because then would be a matter of course.[3] Thus, to abduce from involves determining that is sufficient (or nearly sufficient), but not necessary, for [b, unclear symbol]. For example, the lawn is wet. But if it rained last night, then it would be unsurprising that the lawn is wet. Therefore, by abductive reasoning, the possibility that it rained last night is reasonable. (But note that Peirce did not remain convinced that a single logical form covers all abduction.)[4] Peirce argues that good abductive reasoning from P to Q involves not simply a determination that, e.g., Q is sufficient for P, but also that
Re: Re: Peirce's concept of logical abduction-- a possible moneymaker
Hi Bruno Marchal Cool. Shows you how little I know. Roger Clough, rclo...@verizon.net 11/7/2012 Forever is a long time, especially near the end. -Woody Allen - Receiving the following content - From: Bruno Marchal Receiver: everything-list Time: 2012-11-07, 12:05:11 Subject: Re: Peirce's concept of logical abduction-- a possible moneymaker Hi Roger Clough, Hi Bruno Marchal Yes, by new I mean contingent. But Kant, although his examples are debatable, at least sought a synthetic a priori, which of course would be a gold mine, or perhaps a stairway to the divine. Pragmatism rejects the idea of there being any such universals, but I think by abduction strives to obtain completly new results (if actually new I can't say). I think that's why Peirce came up with the concept of abduction. The concept is very seductive to me for its possible power of discovery of something unknown or new. If comp could do this, I'd not spend a moment more on simulating the brain. Such a program might be worth a lot of money in venues such as AI, the defense industry, medicine and criminal investigation a la Sherlocki Holmes. Abduction is just one technic among many to do inductive inference (predicting theories from fact, synthesizing programs from input-output sequences, finding explanations from data, etc.). The mathematical theory of inductive inference is a very large subfield of theoretical computer science and theoretical artificial Intelligence, or Learning theory. AI is the practice and/or experimental part of it. Behavioral Comp is the idea that machines can emulate all 3p aspect of experience and consciousness. STRONG AI is the thesis that machine can have 1p experience. COMP is the thesis that *you* are emulable by a computer. Famous theorem in theoretical learning theory: Roughly speaking we measure the intelligence (really competence) by the largeness of the class of computable processes recognized (explained, inferred) by a machine, or by the number of such classes (or comobinations). What is *much* more clever than a machine? Answer: two machines. It is the non union theorem of Blum and Blum. Actually, and in general, the gap of intelligence is incomputably big. A machine which can change its mind n times is also incomputably more clever than a machine which changes its mind m times, if m n. (Case and Smith) A surprising result: a machine which is able to change its mind, despite he got a correct theory, is again *much more* clever than a machine which sticks on the correct theory! (Case and Smith). Case Al. refuted also a form of strict Popperianism. Machines able to infer irrefutable theories can learn larger classes, and more classes, of computable process. Most result are, as we could expect, non constructive. No machine can really construct a machine and prove that such machine is more clever than herself. But of course machine can do that serendipitously, and machine can build other hierarchies, close to form of biological self-extension. References below. Theoretical computer science is a *very* large part of mathematical logic. With both a deductive and an inference inductive part. Computer are very peculiar objects. They seem close to what you say about the supreme monads, but the supreme monads are not Gods, they are only God reflector, or God mirror. God is more like the whole truth, I mean the whole arithmetical truth, which contains the many truth concerning many universal numbers and universal relation between numbers. The monads are windows through which God can take a look at itself, but the supreme-monads the universal numbers, are window enough large so that God can begin to recognize itself, so to speak. Bruno BLUM L. BLUM M., 1975, Toward a Mathematical Theory of Inductive Inference. Information and Control 28,.pp. 125-155. CASE J. SMITH C., 1983, Comparison of Identification Criteria for Machine Inductive Inference. In Theoretical Computer Science 25,.pp 193-220. CASE J. NGO-MANGUELLE S., 1979, Refinements of inductive inference by Popperian machines. Tech. Rep., Dept. of Computer Science, State Univ. of New-York, Buffalo. http://en.wikipedia.org/wiki/Abductive_reasoning Abduction[1] is a form of logical inference that goes from data description of something to a hypothesis that accounts for the reliable data and seeks to explain relevant evidence. The term was first introduced by the American philosopher Charles Sanders Peirce (1839?1914) as guessing.[2] Peirce said that to abduce a hypothetical explanation from an observed surprising circumstance is to surmise that may be true because then would be a matter of course.[3] Thus, to abduce from involves determining that is sufficient (or nearly sufficient), but not necessary, for [b, unclear symbol]. For example, the lawn is wet. But if it rained
Re: Re: Peirce's concept of logical abduction-- a possible moneymaker
Hi Stephen P. King Glad to have a fellow enthusiast. Roger Clough, rclo...@verizon.net 11/7/2012 Forever is a long time, especially near the end. -Woody Allen - Receiving the following content - From: Stephen P. King Receiver: everything-list Time: 2012-11-07, 12:02:52 Subject: Re: Peirce's concept of logical abduction-- a possible moneymaker On 11/7/2012 10:13 AM, Roger Clough wrote: Hi Bruno Marchal Yes, by new I mean contingent. But Kant, although his examples are debatable, at least sought a synthetic a priori, which of course would be a gold mine, or perhaps a stairway to the divine. Pragmatism rejects the idea of there being any such universals, but I think by abduction strives to obtain completly new results (if actually new I can't say). I think that's why Peirce came up with the concept of abduction. The concept is very seductive to me for its possible power of discovery of something unknown or new. If comp could do this, I'd not spend a moment more on simulating the brain. Such a program might be worth a lot of money in venues such as AI, the defense industry, medicine and criminal investigation a la Sherlocki Holmes. http://en.wikipedia.org/wiki/Abductive_reasoning Abduction[1] is a form of logical inference that goes from data description of something to a hypothesis that accounts for the reliable data and seeks to explain relevant evidence. The term was first introduced by the American philosopher Charles Sanders Peirce (1839?1914) as guessing.[2] Peirce said that to abduce a hypothetical explanation from an observed surprising circumstance is to surmise that may be true because then would be a matter of course.[3] Thus, to abduce from involves determining that is sufficient (or nearly sufficient), but not necessary, for [b, unclear symbol]. For example, the lawn is wet. But if it rained last night, then it would be unsurprising that the lawn is wet. Therefore, by abductive reasoning, the possibility that it rained last night is reasonable. (But note that Peirce did not remain convinced that a single logical form covers all abduction.)[4] Peirce argues that good abductive reasoning from P to Q involves not simply a determination that, e.g., Q is sufficient for P, but also that Q is among the most economical explanations for P. Simplification and economy are what call for the 'leap' of abduction.[5] In abductive reasoning, unlike in deductive reasoning, the premises do not guarantee the conclusion. Abductive reasoning can be understood as inference to the best explanation.[6] There has been renewed interest in the subject of abduction in the fields of law,[7] computer science, and artificial intelligence research.[8] Dear Roger, I am a HUGE fan of Peirce. I hope to work with you and any one else to elaborate on his ideas. I think that there are no ideal absolutes except only those Hintikka decision games converge to Nash equilibria in some finite number of steps. -- Onward! Stephen -- You received this message because you are subscribed to the Google Groups Everything List group. To post to this group, send email to everything-list@googlegroups.com. To unsubscribe from this group, send email to everything-list+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/everything-list?hl=en.
Re: Peirce's concept of logical abduction-- a possible moneymaker
On 07 Nov 2012, at 18:12, Roger Clough wrote: Hi Bruno Marchal Cool. Shows you how little I know. Those things are virtually unknown by most. Computer science is very technical, and the number of publications is explosive, almost an industry. It is also a gold mine, alas, most philosophy curriculum does not have good courses in the field. We separate the human and the exact sciences, which does not help. In science we still kill the diplomats, and this means that science is still run by unconscious (pseudo)-religion, if not simply the boss is right theory. Of course the degree of graveness is very variable in time and places. Bruno Roger Clough, rclo...@verizon.net 11/7/2012 Forever is a long time, especially near the end. -Woody Allen - Receiving the following content - From: Bruno Marchal Receiver: everything-list Time: 2012-11-07, 12:05:11 Subject: Re: Peirce's concept of logical abduction-- a possible moneymaker Hi Roger Clough, Hi Bruno Marchal Yes, by new I mean contingent. But Kant, although his examples are debatable, at least sought a synthetic a priori, which of course would be a gold mine, or perhaps a stairway to the divine. Pragmatism rejects the idea of there being any such universals, but I think by abduction strives to obtain completly new results (if actually new I can't say). I think that's why Peirce came up with the concept of abduction. The concept is very seductive to me for its possible power of discovery of something unknown or new. If comp could do this, I'd not spend a moment more on simulating the brain. Such a program might be worth a lot of money in venues such as AI, the defense industry, medicine and criminal investigation a la Sherlocki Holmes. Abduction is just one technic among many to do inductive inference (predicting theories from fact, synthesizing programs from input- output sequences, finding explanations from data, etc.). The mathematical theory of inductive inference is a very large subfield of theoretical computer science and theoretical artificial Intelligence, or Learning theory. AI is the practice and/or experimental part of it. Behavioral Comp is the idea that machines can emulate all 3p aspect of experience and consciousness. STRONG AI is the thesis that machine can have 1p experience. COMP is the thesis that *you* are emulable by a computer. Famous theorem in theoretical learning theory: Roughly speaking we measure the intelligence (really competence) by the largeness of the class of computable processes recognized (explained, inferred) by a machine, or by the number of such classes (or comobinations). What is *much* more clever than a machine? Answer: two machines. It is the non union theorem of Blum and Blum. Actually, and in general, the gap of intelligence is incomputably big. A machine which can change its mind n times is also incomputably more clever than a machine which changes its mind m times, if m n. (Case and Smith) A surprising result: a machine which is able to change its mind, despite he got a correct theory, is again *much more* clever than a machine which sticks on the correct theory! (Case and Smith). Case Al. refuted also a form of strict Popperianism. Machines able to infer irrefutable theories can learn larger classes, and more classes, of computable process. Most result are, as we could expect, non constructive. No machine can really construct a machine and prove that such machine is more clever than herself. But of course machine can do that serendipitously, and machine can build other hierarchies, close to form of biological self-extension. References below. Theoretical computer science is a *very* large part of mathematical logic. With both a deductive and an inference inductive part. Computer are very peculiar objects. They seem close to what you say about the supreme monads, but the supreme monads are not Gods, they are only God reflector, or God mirror. God is more like the whole truth, I mean the whole arithmetical truth, which contains the many truth concerning many universal numbers and universal relation between numbers. The monads are windows through which God can take a look at itself, but the supreme-monads the universal numbers, are window enough large so that God can begin to recognize itself, so to speak. Bruno BLUM L. BLUM M., 1975, Toward a Mathematical Theory of Inductive Inference. Information and Control 28,.pp. 125-155. CASE J. SMITH C., 1983, Comparison of Identification Criteria for Machine Inductive Inference. In Theoretical Computer Science 25,.pp 193-220. CASE J. NGO-MANGUELLE S., 1979, Refinements of inductive inference by Popperian machines. Tech. Rep., Dept. of Computer Science, State Univ. of New- York, Buffalo. http://en.wikipedia.org/wiki/Abductive_reasoning Abduction[1] is a form of logical inference that goes
