Search results
Results from the WOW.Com Content Network
Hard science and soft science are colloquial terms used to compare scientific fields on the basis of perceived methodological rigor, exactitude, and objectivity. [ 1 ] [ 2 ] [ 3 ] In general, the formal sciences and natural sciences are considered hard science , whereas the social sciences and other sciences are described as soft science .
Chalmers's hard problem presents a counterexample to this view and to other phenomena like swarms of birds, since it suggests that consciousness, like swarms of birds, cannot be reductively explained by appealing to their physical constituents. Thus, if the hard problem is a real problem then physicalism must be false, and if physicalism is ...
A simple example of an NP-hard problem is the subset sum problem. Informally, if H is NP-hard, then it is at least as difficult to solve as the problems in NP. However, the opposite direction is not true: some problems are undecidable, and therefore even more difficult to solve than all problems in NP, but they are probably not NP-hard (unless ...
In martial arts, the terms hard and soft technique denote how forcefully a defender martial artist counters the force of an attack in armed and unarmed combat.In the East Asian martial arts, the corresponding hard technique and soft technique terms are 硬 (Japanese: gō, pinyin: yìng) and 柔 (Japanese: jū, pinyin: róu), hence Goju-ryu (hard-soft school), Shorinji Kempo principles of go-ho ...
This page was last edited on 16 November 2024, at 12:16 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
The hard-easy effect takes place, for example, when individuals exhibit a degree of underconfidence in answering relatively easy questions and a degree of overconfidence in answering relatively difficult questions. "Hard tasks tend to produce overconfidence but worse-than-average perceptions," reported Katherine A. Burson, Richard P. Larrick ...
A problem is said to be NP-hard if everything in NP can be transformed in polynomial time into it even though it may not be in NP. A problem is NP-complete if it is both in NP and NP-hard. The NP-complete problems represent the hardest problems in NP. If some NP-complete problem has a polynomial time algorithm, all problems in NP do.
Hence, the small set expansion hypothesis, which postulates that SSE is hard to approximate, is a stronger (but closely related) assumption than the unique game conjecture. [25] Some approximation problems are known to be SSE-hard [26] (i.e. at least as hard as approximating SSE).