computer science

Minds and Machines

Minds and Machines is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Minds and Machines rather than just read about it. In short: Minds and Machines is a peer-reviewed academic journal covering artificial intelligence, philosophy, and cognitive science. The journal was established in 1991 with James Henry Fetzer as founding editor-in-chief.

Key takeaways

Minds and Machines belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Minds and Machines to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Minds and Machines from memory before moving on to harder problems.

Reference excerpt

Minds and Machines is a peer-reviewed academic journal covering artificial intelligence, philosophy, and cognitive science. The journal was established in 1991 with James Henry Fetzer as founding editor-in-chief. It was published by Kluwer Academic Publishers but was taken over by Springer in 2021 (Springer Science+Business Media). The journal affiliates with the Society for Machines and Mentality, a special interest group within the International Association for Computing and Philosophy. The current editor-in-chief is Mariarosaria Taddeo (University of Oxford).

Editors Previous editors-in-chief of the journal have been James H. Fetzer (1991–2000), James H. Moor (2001–2010), and Gregory Wheeler (2011–2016).

Abstracting and indexing The journal is abstracted and indexed by the following services:

According to the Journal Citation Reports, the journal has a 2016 impact factor of 0.514.

Controversies Regarding the peer review conducted in 2025, it was revealed that Taddeo and Springer Nature had falsely told the author that the manuscript had been desk-rejected, although peer review had in fact been conducted. It was also revealed that Springer Nature's Research Integrity Director Chris Graf and its Data Protection Office had continuously pressured the author not to raise claims about the matter. Taddeo stated that "serious problems" had occurred with the executive editor who handled the submission, but the journal has not disclosed the specific nature of these problems.

Article categories The journal publishes articles in the categories Research articles, Reviews, Critical and discussion exchanges (debates), Letters to the Editor, and Book reviews.

Frequently cited articles According to the Web of Science, the following five articles have been cited most frequently:

Edelman, S. (1995). "Representation, similarity, and the chorus of prototypes". Minds and Machines. 5: 45–68. doi:10.1007/BF00974189. S2CID 879875. Copeland, B. J. (2002). "Hypercomputation". Minds and Machines. 12 (4): 461–502. doi:10.1023/A:1021105915386. S2CID 218585685. Glymour, C. (1998). "Learning causes: Psychological explanations of causal explanation". Minds and Machines. 8: 39–60. doi:10.1023/A:1008234330618. S2CID 24720518. Floridi, L.; Sanders, J. W. (2004). "On the Morality of Artificial Agents". Minds and Machines. 14 (3): 349–379. CiteSeerX 10.1.1.16.722. doi:10.1023/B:MIND.0000035461.63578.9d. S2CID 5985008. {{cite journal}}: Cite uses deprecated parameter |citeseerx= (help) Hadley, R. F.; Hayward, M. B. (1997). "Strong Semantic Systematicity from Hebbian Connectionist Learning". Minds and Machines. 7: 1–37. doi:10.1023/A:1008252408222. S2CID 8808083.

References

External links Official website

Worked examples

Example 1 — a first encounter with Minds and Machines

Start with the simplest possible case. Write down what Minds and Machines claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Minds and Machines before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Minds and Machines ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Minds and Machines

In research: Minds and Machines appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Minds and Machines in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Minds and Machines is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1991 establishments in the United States, Academic journals established in 1991, Computer science journals, so understanding it makes those chapters shorter.
In everyday life: Look for Minds and Machines outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Minds and Machines in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Minds and Machines means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Minds and Machines out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Minds and Machines in simple terms?

Why does Minds and Machines matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Minds and Machines?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Minds and Machines.