Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Deep reinforcement learningDeep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. Deep RL incorporates deep learning into the solution, allowing agents to make decisions from unstructured input data without manual engineering of the state space. Deep RL algorithms are able to take in very large inputs (e.g.
Nuclear fusion–fission hybridHybrid nuclear fusion–fission (hybrid nuclear power) is a proposed means of generating power by use of a combination of nuclear fusion and fission processes. The basic idea is to use high-energy fast neutrons from a fusion reactor to trigger fission in non-fissile fuels like U-238 or Th-232. Each neutron can trigger several fission events, multiplying the energy released by each fusion reaction hundreds of times. As the fission fuel is not fissile, there is no self-sustaining chain reaction from fission.
Q-learningQ-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the environment (hence "model-free"), and it can handle problems with stochastic transitions and rewards without requiring adaptations. For any finite Markov decision process (FMDP), Q-learning finds an optimal policy in the sense of maximizing the expected value of the total reward over any and all successive steps, starting from the current state.
Learning rateIn machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration while moving toward a minimum of a loss function. Since it influences to what extent newly acquired information overrides old information, it metaphorically represents the speed at which a machine learning model "learns". In the adaptive control literature, the learning rate is commonly referred to as gain. In setting a learning rate, there is a trade-off between the rate of convergence and overshooting.
Plasma (physics)Plasma () is one of four fundamental states of matter, characterized by the presence of a significant portion of charged particles in any combination of ions or electrons. It is the most abundant form of ordinary matter in the universe, being mostly associated with stars, including the Sun. Extending to the rarefied intracluster medium and possibly to intergalactic regions, plasma can be artificially generated by heating a neutral gas or subjecting it to a strong electromagnetic field.
Reversed field pinchA reversed-field pinch (RFP) is a device used to produce and contain near-thermonuclear plasmas. It is a toroidal pinch which uses a unique magnetic field configuration as a scheme to magnetically confine a plasma, primarily to study magnetic confinement fusion. Its magnetic geometry is somewhat different from that of the more common tokamak. As one moves out radially, the portion of the magnetic field pointing toroidally reverses its direction, giving rise to the term reversed field.
Dense plasma focusA dense plasma focus (DPF) is a type of plasma generating system originally developed as a fusion power device starting in the early 1960s. The system demonstrated scaling laws that suggested it would not be useful in the commercial power role, and since the 1980s it has been used primarily as a fusion teaching system, and as a source of neutrons and X-rays. The original concept was developed in 1954 by N.V. Filippov, who noticed the effect while working on early pinch machines in the USSR.
Nuclear fusionNuclear fusion is a reaction in which two or more atomic nuclei, usually deuterium and tritium (hydrogen variants), are combined to form one atomic nuclei and subatomic particles (neutrons or protons). The difference in mass between the reactants and products is manifested as either the release or absorption of energy. This difference in mass arises due to the difference in nuclear binding energy between the atomic nuclei before and after the reaction.
Big dataBig data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.
