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AI field of problem generation and solving
Generative Problem Solving (GPS) is an area of artificial intelligence that is concerned with the generation, representation, verification, and solution
Generative_Problem_Solving
Type of large language model
A generative pre-trained transformer (GPT) is a type of large language model (LLM) that is widely used in generative artificial intelligence chatbots.
Generative pre-trained transformer
Generative_pre-trained_transformer
Generative AI chatbot by OpenAI
generative AI chatbot developed by OpenAI. Originally released on November 30, 2022, the product uses large language models – specifically generative
ChatGPT
AI that generates content
Generative artificial intelligence (GenAI) is a subfield of artificial intelligence (AI) that uses generative models to generate text, images, videos
Generative_AI
Machine learning framework
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative AI. The concept
Generative adversarial network
Generative_adversarial_network
Topics referred to by the same term
fairly share computer processing time General Problem Solver, a 1959 computer program Generative Problem Solving, field of artificial intelligence Crossroads
GPS_(disambiguation)
2026 large language model by OpenAI
GPT-5.6 (Generative Pre-trained Transformer 5.6) is a set of large language models (LLMs) developed by OpenAI and released on July 9, 2026. It is a family
GPT-5.6
Mental process of problem solving
Creative problem-solving is the mental process of searching for an original and previously unknown solution to a problem. To qualify, the solution must
Creative_problem-solving
Study of nature's complex behaviour systems
Generative science is an area of research that explores the natural world and its complex behaviours. It explores ways "to generate apparently unanticipated
Generative_science
Model for generating observable data in probability and statistics
Generative models are a class of computational models frequently used for classification. In machine learning, it typically models the joint distribution
Generative_model
Intelligence in machines
typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is also a field of research spanning
Artificial_intelligence
Taiwanese American Professor
Ramamoorthy. Sheu's current research is about semantic computing and Generative Problem Solving (GPS), an extension of semantic computing that bridges modern
Phillip_C.-Y._Sheu
Optimization problem
instances. Additional methods for solving the VRP have been proposed, some of which depend on the specific problem conditions. In the case of a VRP with
Vehicle_routing_problem
Period of rapid progress in AI
intelligence beginning in the mid-2010s and accelerating in the 2020s. Generative AI technologies include large language models (LLM), which generate text
AI_boom
Large Language Models" (PDF). Ulam.ai. Lee, Melissa (9 August 2026). "Generative AI has changed mathematics forever. Where to from here?". The Conversation
List of mathematical discoveries made with artificial intelligence
List_of_mathematical_discoveries_made_with_artificial_intelligence
Mathematical model for sequential decision making under uncertainty
by solving the Hamilton–Jacobi–Bellman (HJB) partial differential equation. In order to discuss the HJB equation, we need to reformulate our problem V
Markov_decision_process
Research program in theoretical linguistics
Generative semantics was a research program in theoretical linguistics which held that syntactic structures are computed on the basis of meanings rather
Generative_semantics
Iterative design process
Generative design is an iterative design process that uses software to generate outputs that fulfill a set of constraints iteratively adjusted by a designer
Generative_design
Use of functions that call themselves
method of solving a computational problem where the solution depends on solutions to smaller instances of the same problem. Recursion solves such recursive
Recursion_(computer_science)
2026 release of AI-generated mathematical solutions
controversy, in which the company's claim to solving the Navier–Stokes existence and smoothness problem under certain conditions was criticized for taking
OpenAI bulk release of mathematical papers
OpenAI_bulk_release_of_mathematical_papers
Computer hardware technology that uses quantum mechanics
good for solving complex quantum many-body problems and thus may apply to applications involving quantum chemistry. Quantum-enhanced generative models including
Quantum_computing
Numerical method for solving physical or engineering problems
popular method for numerically solving differential equations arising in engineering and mathematical modeling. Typical problem areas of interest include the
Finite_element_method
Process of generating creative ideas
Philosophy portal Psychology portal Lateral thinking – Manner of solving problems Dyson, Scott Benjamin; Chang, Yu-Lin; Chen, Hsueh-Chih; Hsiung, Hsiang-Yu;
Divergent_thinking
Organizational model
creates more generative conversations. People use appreciative inquiry to solve problems, but they do it through generativity, not problem-solving. There are
Appreciative_inquiry
Reusable solution template to a commonly-needed software behavior
unnecessary in languages that have built-in support for solving the problem they are trying to solve, and object-oriented patterns are not necessarily suitable
Software_design_pattern
Creative process of generating, developing, and communicating new ideas
Originality Jonson, 2005, page 613 Graham and Bachmann, 2004, p. 54 "How Generative AI Can Augment Human Creativity". Harvard Business Review. 16 June 2023
Ideation_(creative_process)
Mathematical method for optimizing material layout under given conditions
methodologies that have been used to solve topology-optimization problems. Solving topology-optimization problems in a discrete sense is done by discretizing
Topology_optimization
Mathematical model used for classification or regression
prediction error under a chosen loss function. They are often contrasted with generative models, which aim to model how the data are generated and can be used
Discriminative_model
Technique for the generative modeling of a continuous probability distribution
also known as diffusion-based generative models or score-based generative models, are a class of latent variable generative models. A diffusion model consists
Diffusion_model
Image-generating machine learning model
Retrieved 2026-02-27. "Nvidia and Adobe think they may have solved generative A.I.'s copyright problem". Yahoo Finance. 2023-03-22. published, Craig Hale (2025-10-29)
Adobe_Firefly
Methods devised to encourage creative actions
methods of re-framing problems, changes in the affective environment and so on. They can be used as part of problem solving, artistic expression, or
Creativity_techniques
2023 text-generating language model
Generative Pre-trained Transformer 4 (GPT-4) is a large language model developed by OpenAI and the fourth in its series of GPT foundation models. GPT-4
GPT-4
Machine learning model training problem
Batch normalization is a standard method for solving both the exploding and the vanishing gradient problems. In multi-level hierarchy of networks (Schmidhuber
Vanishing_gradient_problem
Act of staging or presenting a form of entertainment
adaptation of eight areas: Handling crisis, managing stress, creative problem solving, knowing necessary functional tools and skills, agile management of
Performance
Mathematical puzzle game
of LLM Generative AI programs. The researchers found that the leading AI models, including ChatGPT, Claude, and Deepseek, struggled with solving a Tower
Tower_of_Hanoi
AI benchmark testbed for mathematical problem solving
their attempts to solve 14 bespoke heretofore unexamined mathematical problems (none of which are on the scale of the Millennium Problems). It was established
FrontierMath
Machine learning paradigm
input, denoted by p ( y ∣ x ) {\displaystyle p(y\mid x)} ). To solve a given problem of supervised learning, the following steps must be performed: Determine
Supervised_learning
Test to determine whether a user is human
a Human Into Solving a CAPTCHA". Gizmodo. Archived from the original on 11 April 2023. Retrieved 11 April 2023. "Top 10 Captcha Solving Services Compared"
CAPTCHA
American artificial intelligence company
San Francisco, California. It develops "frontier" generative AI models, particularly its generative pre-trained transformer (GPT) series of large language
OpenAI
Paradigm in machine learning
sample problems that the teacher solves for the class as an aid in solving another set of problems. In the transductive setting, these unsolved problems act
Weak_supervision
program called the "General Problem Solver". Other "searching" programs accomplished impressive results like solving problems in geometry and algebra, such
History of artificial intelligence
History_of_artificial_intelligence
Difficulties arising when analyzing data with many aspects ("dimensions")
of the combinatorics problems above and the distance function problems explained below. When solving dynamic optimization problems by numerical backward
Curse_of_dimensionality
Philosophical problem
<https://www.philosophypages.com/dy/index.htm> Mayer, Richard E. Thinking, Problem Solving, Cognition. 2nd ed. New York, NY: W. H. Freeman and Company, 1991.
Plato's_problem
Statistical classification in machine learning
function R is convex, then the above is a convex problem. Many algorithms exist for solving such problems; popular ones for linear classification include
Linear_classifier
Methods in artificial intelligence research
from sequences of basic problem-solving actions. Good macro-operators simplify problem-solving by allowing problems to be solved at a more abstract level
Symbolic artificial intelligence
Symbolic_artificial_intelligence
Large language model
OpenAI o3 is a generative pre-trained transformer (GPT) model developed by OpenAI as a successor to OpenAI o1 for ChatGPT. It is designed to devote additional
OpenAI_o3
Subset of evolutionary computation
Nicola; Lucas, Simon (eds.), "How a Generative Encoding Fares as Problem-Regularity Decreases", Parallel Problem Solving from Nature – PPSN X, LNCS 5199,
Evolutionary_algorithm
Theory of learning a second language
The generative approach to second language (L2) acquisition (SLA) is a cognitive based theory of SLA that applies theoretical insights developed from within
Generative second-language acquisition
Generative_second-language_acquisition
Statistical model used in machine learning
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing
Flow-based_generative_model
Maintenance service of electronic consumers
Tier I personnel in solving basic technical problems and for investigating elevated issues by confirming the validity of the problem and seeking known solutions
Technical_support
2024 AI LLM with enhanced reasoning
OpenAI o1 is a generative pre-trained transformer (GPT), the first in OpenAI's "o" series of reasoning models. A preview of o1 was released by OpenAI on
OpenAI_o1
Process of understanding a design's impact on an audience
classifying user research. Generative research or exploratory research is done to understand and define the problems to solve for users in the first place
User_research
2025 multimodal model by OpenAI
large language model developed by OpenAI and the fifth in its series of generative pre-trained transformer (GPT) foundation models. Preceded in the series
GPT-5
anonymous. Third, in collective intelligence, as in the standard model of problem-solving, there is a beginning, when the central controller broadcasts the question
Collaborative_intelligence
AI's tendency to abruptly and drastically forget old info after learning new info
S2CID 18745466. Dietterich, T. G.; Bakiri, G. (1 January 1995). "Solving Multiclass Learning Problems via Error-Correcting Output Codes". Journal of Artificial
Catastrophic_interference
Pedagogy of computer science
guide students problem-solving and creative abilities tend to help them succeed in computer science and other classes. The problem-solving aspect of computer
Computing_education
Novel generative adversarial network
The Style Generative Adversarial Network, or StyleGAN for short, is an extension to the GAN architecture introduced by Nvidia researchers in December 2018
StyleGAN
Plan for the construction of an object or system
dominant but different views of the design process: as a rational problem-solving process and as a process of reflection-in-action. They suggested that
Design
Machine learning model
A text-to-video model is a form of generative AI that uses a natural language description as input to produce a video relevant to the input text. Advancements
Text-to-video_model
Thinking technique that involves an analytical approach to problem solving
thinking encourages individuals to employ a sequential approach to solving problem where a creative and multidirectional response are seen as imprudent
Vertical_thinking
Theory of perception
of problem solving. Max Wertheimer distinguished two kinds of thinking: productive thinking and reproductive thinking. Productive thinking is solving a
Gestalt_psychology
Annual computer programming event
have used generative artificial intelligence to solve the puzzles. In 2023, Wastl requested that users abstain from using these tools to solve the puzzles
Advent_of_Code
Blending of various AI techniques
accuracy, improved robustness, and enhanced capabilities in solving diverse and challenging problems. Agents and Artificial Intelligence: 12th International
Blended artificial intelligence
Blended_artificial_intelligence
Group creativity technique
executive Alex Faickney Osborn began developing methods for creative problem-solving. He was frustrated by employees' inability to develop creative ideas
Brainstorming
2026 scientific priority controversy
Institute listed solving one of four instances of the Navier–Stokes existence and smoothness problem as one of the Millennium Prize Problems and pledged to
Navier–Stokes priority controversy
Navier–Stokes_priority_controversy
(TAEMS or TÆMS) is a problem domain independent modeling language used to describe the task structures and the problem-solving activities of intelligent
Task analysis environment modeling simulation
Task_analysis_environment_modeling_simulation
way of other units. Rather than improve the Game AI to properly solve a difficult problem in the virtual environment, it is often more cost-effective to
Artificial intelligence in video games
Artificial_intelligence_in_video_games
Branch of machine learning
belief networks, recurrent neural networks, convolutional neural networks, generative adversarial networks, transformers, and neural radiance fields. These
Deep_learning
20th-century dispute among American linguists
arguing that the approach created more problems than it solved. These limitations led to the decline of generative semantics. After the protracted debates
Linguistics_wars
optimization posing their own specific challenges in formulating and solving the resulting problems; these include, shape optimization, wing-shape optimization
Design_optimization
Artificial intelligence concept
existed in the task files, and if so, simply return it rather than solving the problem. To detect such behavior, researchers have suggested several methodologies
Reward_hacking
Australian and American mathematician (born 1975)
In 1990, at age 15, he wrote his first mathematical book, Solving Mathematical Problems: A Personal Perspective, which was published in 1992. He graduated
Terence_Tao
have for decades been trying to use AI and computers to help solve mathematics problems. The impact of AI has been pronounced in mathematics, where results
Mathematics and artificial intelligence
Mathematics_and_artificial_intelligence
Type of machine learning model
LLMs are typically based on the transformer neural network architecture. Generative pre-trained transformers (GPTs) are a type of LLM that is pre-trained
Large_language_model
Discrete search algorithms Uninformed search Brute force search – Problem-solving technique and algorithmic paradigmPages displaying short descriptions
Outline of artificial intelligence
Outline_of_artificial_intelligence
Structuring text as input to generative artificial intelligence
language inputs (known as prompts) to produce specified outputs from a generative AI model. Context engineering is the related area of software engineering
Prompt_engineering
Process of developing trajectory performance
parameter optimization problem, 3) Solve that optimization problem. Direct method A direct method for solving a trajectory optimization problem consists of two
Trajectory_optimization
Processes by which design concepts are developed
three-dimensional problem solving, Bryan Lawson found architects employed solution-focused cognitive strategies, distinct from the problem-focused strategies
Design_thinking
Toyota Production System principle
a key approach in problem-solving, saying that if the problem exists on the shop floor, then it needs to be understood and solved at the shop floor.
Genchi_genbutsu
Equation in machine learning
\mathbf {h} _{\text{in}}} of the neural ODE is obtained by solving the initial value problem d h ( t ) d t = f θ ( h ( t ) , t ) , h ( 0 ) = h in , {\displaystyle
Neural_differential_equation
Process of development of new products
design, particularly when matters of functionality or utility (e.g. problem-solving) are at issue, though such boundaries are not always clear. There are
Product_design
planning and increasing efficiency and productivity. The advances in generative design through the input of specific prompts allow architects to produce
Artificial intelligence in architecture
Artificial_intelligence_in_architecture
Chatbot developed by Google
sometimes marketed as Google Gemini and originally known as Bard, is a generative artificial intelligence chatbot and virtual assistant developed by Google
Google_Gemini
Multidisciplinary endeavour
where simple mechanical models were built to explore mathematical problem solving. Professional interest in the creative aspect of computation also was
Computational_creativity
Computer programming textbook by Matthias Felleisen and colleagues
process, and generative recursion, where new problem data is generated in the middle of the problem-solving process and the problem solving method is re-used
How_to_Design_Programs
List of concepts in artificial intelligence
to that of solving the central artificial intelligence problem—making computers as intelligent as people, or strong AI. To call a problem AI-complete
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
GPU microarchitecture designed by Nvidia
These areas have influenced or are implemented in transformer-based generative AI model designs or their training algorithms. Blackwell was the first
Blackwell_(microarchitecture)
Method in education
students' interactions with the problem situation and learning is assessed via these emergent behaviors. In a generative activity, students are asked to
Formative_assessment
American author and creative director
techie should read". "Adobe's Chris Duffey on AI, creativity in solving business problems and pigeons". The Drum. Retrieved 2019-10-29. "Chris Duffey".
Chris_Duffey
Large language model designed for reasoning tasks
sub-agents for reasoning and execution, enabling more scalable multi-step problem-solving than a with single sequential reasoning chain. However, both Kimi models
Reasoning_model
Type of database that uses vectors to represent other data
databases to power generative AI apps". TechCrunch. Retrieved 2026-01-01. "5 Hard Problems in Vector Search, and How Cassandra Solves Them". TheNewStack
Vector_database
distortions or alterations. Many techniques have been proposed to solve the audio inpainting problem and this is usually achieved by analyzing the temporal and
Audio_inpainting
2017 paper conceptualizing the transformer-based deep learning architecture
other tasks like question answering and what is now known as multimodal generative AI. Some early examples on which the team tried their Transformer architecture
Attention_Is_All_You_Need
AI customization approach
knowledge from problem solving knowledge—examples thereof are the constraint satisfaction problem, the Boolean satisfiability problem, and different answer
Knowledge-based_configuration
Generative encoding that evolves artificial neural networks
Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used NeuroEvolution
HyperNEAT
Approach to design that considers human needs at every step of development
Human-centered design, as used in ISO standards, is an approach to problem-solving commonly used in process, product, service and system design, management
Human-centered_design
Competence to evaluate AI technologies
including self-driving automobiles, virtual assistants and text generation by generative AI models. Users of these tools should be able to make informed decisions
AI_literacy
1965 book by Noam Chomsky
presented a deeper, more extensive reformulation of transformational generative grammar (TGG), a new kind of syntactic theory that he had introduced in
Aspects of the Theory of Syntax
Aspects_of_the_Theory_of_Syntax
Reverse-engineering without infringing copyright
ISSN 0199-6649. Rachel Parker (28 September 1987). "'Secured Facility' Solves Compatibility Conflicts". InfoWorld: The Newspaper for the Microcomputing
Clean-room_design
learning environments (such as interactive science simulations or problem solving scenarios) . CATLM expands on Mayer's Cognitive Theory of Multimedia
Cognitive-Affective Theory of Learning with Media
Cognitive-Affective_Theory_of_Learning_with_Media
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GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
GENERATIVE PROBLEM-SOLVING
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