Reasoning Task
A Reasoning Task is an problem-solving task that accepts a reasoning query plus supporting evidence, and is then required to provide reasoned argument (that culminates in a conclusion or inference).
- Context:
- Input: Evidence.
- output: A Reasoned Argument (premises and conclusions; Inference).
- measure: Reasoning Accuracy.
- ...
- It can range from being a Quantitative Reasoning Task to being a Qualitative Reasoning Task to being a Logical Reasoning Task.
- It can range from being a Deductive Reasoning Task to being an Inductive Reasoning Task to being an Abductive Reasoning Task, depending on the reasoning pattern constraint.
- It can range from being a Logical Inference Task to being a Statistical Inference Task, based on required inference style.
- It can range from being an Exact Reasoning Task to being an Approximate Reasoning Task, based on precision requirements.
- It can range from being a Reasoning With Certainty to being a Reasoning Under Uncertainty.
- It can range from being a Open-Domain Reasoning Task to being a Domain-Specific Reasoning Task.
- It can range from being a Constraint-based Reasoning Task to being a Heuristic-based Reasoning Task.
- It can range from being a Practical Reasoning Task to being a Theoretical Reasoning Task.
- It can range from being an Analytical Reasoning Task to being a Creative Reasoning Task.
- It can range from being a Quantitative Reasoning Task to being a Qualitative Reasoning Task to being a Logical Reasoning Task.
- It can range from being a Deductive Reasoning Task, to being an Inductive Reasoning Task, to being an Abductive Reasoning Task, depending on the reasoning pattern constraint.
- It can range from being a Logical Inference Task to being a Statistical Inference Task, based on required inference style.
- It can range from being an Exact Reasoning Task to being an Approximate Reasoning Task, based on precision requirements.
- It can range from being a Reasoning With Certainty to being a Reasoning Under Uncertainty.
- It can range from being a Open-Domain Reasoning Task to being a Domain-Specific Reasoning Task.
- It can range from being a Constraint-based Reasoning Task to being a Heuristic-based Reasoning Task.
- It can range from being a Practical Reasoning Task to being a Theoretical Reasoning Task.
- It can range from being an Analytical Reasoning Task to being a Creative Reasoning Task.
- ...
- It can be solved by a Reasoning Entity (with reasoning skill that implements a reasoning algorithm).
- It can be instantiated in a Reasoning Act.
- ...
- Example(s):
- Formal Reasoning Tasks, such as:
- A Deductive Reasoning Task, such as: "Is Socrates mortal?" given the facts: "Socrates is a person," and the rule "if person then mortal."
- A Logical Inference Task, such as: "Determine if the given argument is valid based on logical premises." Evaluating logical structures.
- A Mathematical Proof Task, such as: "Prove that the sum of the angles in a triangle is 180 degrees using geometric principles." Applying mathematical principles to prove geometric theorems.
- Empirical Reasoning Tasks, such as:
- A Statistical Inference Task, such as: "Estimate the population mean from the sample data." Making predictions based on statistical data.
- An Inductive Generalization Task, such as: "Based on this sample data, predict the trend for the entire population." Generalizing from specific observations.
- A Causal Reasoning Task, such as: "Given these symptoms, what is the most likely diagnosis?" Inferring the most plausible explanation based on causal relationships.
- Diagnostic Reasoning Tasks, such as:
- A Medical Diagnostic Reasoning Task, such as: "Interpret the patient's symptoms and medical history to diagnose the illness." Using medical evidence to diagnose a patient's condition.
- A Historical Analysis Task, such as: "Infer the most plausible explanation for a past event given incomplete information." Analyzing historical evidence to make informed conclusions.
- Domain-Specific Reasoning Tasks, such as:
- An Economic Reasoning Task, such as: "Predict market trends based on past data." Using economic models and data to forecast market behavior.
- A Legal Reasoning Task, such as: "Evaluate the witness testimonies and evidence to determine the guilt or innocence of the accused." Analyzing legal evidence to formulate arguments and make judgments in a court case.
- A Scientific Reasoning Task, such as: "Analyze the experimental data to determine if it supports the hypothesis that this new drug is effective." Evaluating the evidence from scientific experiments to draw conclusions about the effectiveness of a new drug.
- Healthcare Reasoning Tasks, such as: "Diagnose this medical condition based on patient data.".
- ...
- Perceptual Reasoning Tasks, such as:
- A Perceptual Inference Task, such as: "Infer depth from stereoscopic vision." Using visual cues to determine spatial relationships.
- A Natural Language Inference Task, such as: "Determine if a sentence logically follows from another." Analyzing language to infer logical relationships.
- A Commonsense Reasoning Task, such as: "Infer that if someone is running in the rain, they might be wet." Using everyday knowledge to make logical inferences.
- A Temporal Reasoning Task, such as: "Determine the sequence of events in a story." Analyzing temporal data to infer order of occurrences.
- Analytical Reasoning Tasks, such as:
- An Exact Reasoning Task, such as: "Calculate the precise value of pi to 20 decimal places." Requiring high precision.
- An Approximate Reasoning Task, such as: "Estimate the number of people in a crowded room." Allowing for estimation.
- An Analytical Reasoning Task, such as: "Analyze the financial report to identify trends." Systematic analysis.
- Creative Reasoning Tasks, such as:
- A Creative Reasoning Task, such as: "Design an innovative product to meet market needs." Using creative thinking to solve problems.
- Practical Reasoning Tasks, such as:
- A Practical Reasoning Task, such as: "Plan the budget for this project." Practical application.
- A Theoretical Reasoning Task, such as: "Explore the implications of a new theory in physics." Abstract thinking.
- Constraint-Based Reasoning Tasks, such as:
- A Constraint-based Reasoning Task, such as: "Solve this puzzle by following these specific rules." Strict constraints.
- A Heuristic-based Reasoning Task, such as: "Find the best route for delivery using a heuristic algorithm." Using rules of thumb.
- Reasoning with Certainty tasks, such as: "Prove that the sum of the angles in a triangle is always 180 degrees." Conclusive proof.
- Reasoning Under Uncertainty tasks, such as: "Determine the probability of rain tomorrow." Based on probabilistic models.
- Open-Domain Reasoning Tasks, such as: "Solve this general logic puzzle." Broad applicability.
- ...
- Formal Reasoning Tasks, such as:
- Counter-Example(s):
- a Decision Task (different result, process).
- an Analysis Task (broader).
- a Semantic Modeling Task.
- See: Logical Inference, Mathematical Inference, Empirical Inference, Inductive Inference, Deductive Inference, Abductive Inference, Non-Monotonic Reasoning, Textual Inference, Background Knowledge.
References
2023
- (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Reason Retrieved:2023-8-9.
- Reason is the capacity of applying logic consciously by drawing conclusions from new or existing information, with the aim of seeking the truth. It is closely associated with such characteristically human activities as philosophy, science, language, mathematics, and art, and is normally considered to be a distinguishing ability possessed by humans. [1] Reason is sometimes referred to as rationality. [2] Reasoning is associated with the acts of thinking and cognition, and involves the use of one's intellect. The field of logic studies the ways in which humans can use formal reasoning to produce logically valid arguments. Reasoning may be subdivided into forms of logical reasoning, such as deductive reasoning, inductive reasoning, and abductive reasoning. Aristotle drew a distinction between logical discursive reasoning (reason proper), and intuitive reasoning, in which the reasoning process through intuition—however valid—may tend toward the personal and the subjectively opaque. In some social and political settings logical and intuitive modes of reasoning may clash, while in other contexts intuition and formal reason are seen as complementary rather than adversarial. For example, in mathematics, intuition is often necessary for the creative processes involved with arriving at a formal proof, arguably the most difficult of formal reasoning tasks. Reasoning, like habit or intuition, is one of the ways by which thinking moves from one idea to a related idea. For example, reasoning is the means by which rational individuals understand sensory information from their environments, or conceptualize abstract dichotomies such as cause and effect, truth and falsehood, or ideas regarding notions of good or evil. Reasoning, as a part of executive decision making, is also closely identified with the ability to self-consciously change, in terms of goals, beliefs, attitudes, traditions, and institutions, and therefore with the capacity for freedom and self-determination. [3] In contrast to the use of "reason" as an abstract noun, a reason is a consideration given which either explains or justifies events, phenomena, or behavior.[4] Reasons justify decisions, reasons support explanations of natural phenomena; reasons can be given to explain the actions (conduct) of individuals. Using reason, or reasoning, can also be described more plainly as providing good, or the best, reasons. For example, when evaluating a moral decision, "morality is, at the very least, the effort to guide one's conduct by reason—that is, doing what there are the best reasons for doing—while giving equal [and impartial] weight to the interests of all those affected by what one does." [5]
Psychologists and cognitive scientists have attempted to study and explain how people reason, e.g. which cognitive and neural processes are engaged, and how cultural factors affect the inferences that people draw. The field of automated reasoning studies how reasoning may or may not be modeled computationally. Animal psychology considers the question of whether animals other than humans can reason.
- Reason is the capacity of applying logic consciously by drawing conclusions from new or existing information, with the aim of seeking the truth. It is closely associated with such characteristically human activities as philosophy, science, language, mathematics, and art, and is normally considered to be a distinguishing ability possessed by humans. [1] Reason is sometimes referred to as rationality. [2] Reasoning is associated with the acts of thinking and cognition, and involves the use of one's intellect. The field of logic studies the ways in which humans can use formal reasoning to produce logically valid arguments. Reasoning may be subdivided into forms of logical reasoning, such as deductive reasoning, inductive reasoning, and abductive reasoning. Aristotle drew a distinction between logical discursive reasoning (reason proper), and intuitive reasoning, in which the reasoning process through intuition—however valid—may tend toward the personal and the subjectively opaque. In some social and political settings logical and intuitive modes of reasoning may clash, while in other contexts intuition and formal reason are seen as complementary rather than adversarial. For example, in mathematics, intuition is often necessary for the creative processes involved with arriving at a formal proof, arguably the most difficult of formal reasoning tasks. Reasoning, like habit or intuition, is one of the ways by which thinking moves from one idea to a related idea. For example, reasoning is the means by which rational individuals understand sensory information from their environments, or conceptualize abstract dichotomies such as cause and effect, truth and falsehood, or ideas regarding notions of good or evil. Reasoning, as a part of executive decision making, is also closely identified with the ability to self-consciously change, in terms of goals, beliefs, attitudes, traditions, and institutions, and therefore with the capacity for freedom and self-determination. [3] In contrast to the use of "reason" as an abstract noun, a reason is a consideration given which either explains or justifies events, phenomena, or behavior.[4] Reasons justify decisions, reasons support explanations of natural phenomena; reasons can be given to explain the actions (conduct) of individuals. Using reason, or reasoning, can also be described more plainly as providing good, or the best, reasons. For example, when evaluating a moral decision, "morality is, at the very least, the effort to guide one's conduct by reason—that is, doing what there are the best reasons for doing—while giving equal [and impartial] weight to the interests of all those affected by what one does." [5]
2013
- (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Inference
- Inference is the act or process of deriving logical conclusions from premises known or assumed to be true.[6] The conclusion drawn is also called an idiomatic. The laws of valid inference are studied in the field of logic.
Human inference (i.e. how humans draw conclusions) is traditionally studied within the field of cognitive psychology; artificial intelligence researchers develop automated inference systems to emulate human inference. ...
- Inference is the act or process of deriving logical conclusions from premises known or assumed to be true.[6] The conclusion drawn is also called an idiomatic. The laws of valid inference are studied in the field of logic.
2013
- http://en.wikipedia.org/wiki/Inference#Definition_of_inference
- The process by which a conclusion is inferred from multiple observations is called inductive reasoning. The conclusion may be correct or incorrect, or correct to within a certain degree of accuracy, or correct in certain situations. Conclusions inferred from multiple observations may be tested by additional observations.
This definition is disputable (due to its lack of clarity. Ref: Oxford English dictionary: "induction ... 3. Logic the inference of a general law from particular instances.") The definition given thus applies only when the "conclusion" is general.
- A conclusion reached on the basis of evidence and reasoning.
- The process of reaching such a conclusion: "order, health, and by inference cleanliness".
- The process by which a conclusion is inferred from multiple observations is called inductive reasoning. The conclusion may be correct or incorrect, or correct to within a certain degree of accuracy, or correct in certain situations. Conclusions inferred from multiple observations may be tested by additional observations.
2012
- http://en.wikipedia.org/wiki/Reason
- Reason is a term that refers to the capacity human beings have to make sense of things, to establish and verify facts, and to change or justify practices, institutions, and beliefs. ...
- ↑ Compare:
- ↑ See, for example: * * * *
- ↑ Michel Foucault, "What is Enlightenment?" in The Essential Foucault, eds. Paul Rabinow and Nikolas Rose, New York: The New Press, 2003, 43–57. See also Nikolas Kompridis, "The Idea of a New Beginning: A Romantic Source of Normativity and Freedom," in Philosophical Romanticism, New York: Routledge, 2006, 32–59; "So We Need Something Else for Reason to Mean", International Journal of Philosophical Studies 8: 3, 271–295.
- ↑ Merriam-Webster.com Merriam-Webster Dictionary definition of reason
- ↑ Rachels, James. The Elements of Moral Philosophy, 4th ed. McGraw Hill, 2002
- ↑ http://www.thefreedictionary.com/inference
2009
- http://en.wiktionary.org/wiki/Reasoning
- S: (n) reasoning, logical thinking, abstract thought (thinking that is coherent and logical)
- S: (v) reason, reason out, conclude (decide by reasoning; draw or come to a conclusion) "We reasoned that it was cheaper to rent than to buy a house"
- S: (v) argue, reason (present reasons and arguments)
- S: (v) reason (think logically) "The children must learn to reason"
- S: (adj) intelligent, reasoning, thinking (endowed with the capacity to reason)
- http://en.wiktionary.org/wiki/reasoning
- Noun
- 1. Action of the verb to reason.
- 2. The deduction of inferences or interpretations from premises; abstract thought; ratiocination.
- Verb
- 1. Present participle of reason.
- Noun
2009
- (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Reasoning
- Reasoning is the cognitive process of looking for reasons for beliefs, conclusions, actions or feelings. [1]
- Humans have the ability to engage in reasoning about their own reasoning. Different forms of such reflection on reasoning occur in different fields. In philosophy, the study of reasoning typically focuses on what makes reasoning efficient or inefficient, appropriate or inappropriate, good or bad. Philosophers do this by either examining the form or structure of the reasoning within arguments, or by considering the broader methods used to reach particular goals of reasoning. Psychologists and cognitive scientists, in contrast, tend to study how people reason, which cognitive and neural processes are engaged, how cultural factors affect the inferences people draw. The properties of logics which may be used to reason are studied in mathematical logic. The field of automated reasoning studies how reasoning may be modelled computationally. Lawyers also study reasoning.
2009
- http://www.uky.edu/~rosdatte/phi120/glossary.htm
- inference: A jump of reasoning from known information to new information. (See inferential relationship)
2009
- http://clopinet.com/isabelle/Projects/ETH/Exam_Questions.html
- Inference refers to the ability of a learning system, namely going from the "particular" (the examples) to the "general" (the predictive model). In the best of all worlds, we would not need to worry about model selection. Inference would be performed in a single step: we input training examples into a big black box containing all models, hyper-parameters, and parameters; outcomes the best possible trained model. In practice, we often use 2 levels of inference: we split the training data into a training set and a validation set. The training set serves the trains at the lower level (adjust the parameters of each model); the validation set serves to train at the higher level (select the model.) Nothing prevents us for using more than 2 levels. However, the price to pay will be to get smaller data sets to train with at each level.