Search results
Results From The WOW.Com Content Network
Given a training set consisting of examples = (,, ′), where , ′ are observations of a world state from two consecutive time steps , ′ and is an action instance observed in time step , the goal of action model learning in general is to construct an action model , , where is a description of domain dynamics in action description formalism like STRIPS, ADL or PDDL and is a probability ...
One such example is the Executive Action-Learning (EAL) Model which originated in the United States in 2005. The EAL model differs from the traditional organizational training methods by shifting the focus from professor-led, general knowledge memorization and presentations to executive-led and project-based experiential reflection and problem ...
Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behavior in an agent environment.
In psychology, the four stages of competence, or the "conscious competence" learning model, relates to the psychological states involved in the process of progressing from incompetence to competence in a skill. People may have several skills, some unrelated to each other, and each skill will typically be at one of the stages at a given time.
The taxonomy divides learning objectives into three broad domains: cognitive (knowledge-based), affective (emotion-based), and psychomotor (action-based), each with a hierarchy of skills and abilities. These domains are used by educators to structure curricula, assessments, and teaching methods to foster different types of learning.
A third example of experiential learning involves learning how to ride a bike, [13] a process which can illustrate the four-step experiential learning model (ELM) as set forth by Kolb [14] and outlined in Figure 1 below. Following this example, in the "concrete experience" stage, the learner physically interacts with the bike in the "here and ...
Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...
Action research is an interactive inquiry process that balances problem-solving actions implemented in a collaborative context with data-driven collaborative analysis or research to understand underlying causes enabling future predictions about personal and organizational change.