AI News, Machine Learning Methods for Planning

Machine Learning Methods for Planning

Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling.

This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning.

Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks.

Problem solving

Problem solving consists of using generic or ad hoc methods, in an orderly manner, to find solutions to problems.

D'Zurilla in 1988 defined problem solving as a 'cognitive–affective–behavioral process through which an individual (or group) attempts to identify, discover, or invent effective means of coping with problems encountered in every day living'.[2] It is an evolutionary drive for living organisms and an important coping skill for dealing with a variety of concerns.

Problem solving specifically in psychology refers to a state of desire for reaching a definite 'goal' from a present condition that either is not directly moving toward the goal, is far from it, or needs more complex logic for finding a missing description of conditions or steps toward the goal.

Distinguished feature of a problem is that there is a goal to be reached and how you get there depends upon problem orientation (problem-solving coping style and skills) and systematic analysis.[3] The nature of human problem solving processes and methods is a field of study and work for mental health professionals.

Social psychologists look into the person-environment relationship aspect of the problem and independent and interdependent problem-solving methods.[4] Problem solving has been defined as a higher-order cognitive process and intellectual function that requires the modulation and control of more routine or fundamental skills.[5] Problem solving has two major domains: mathematical problem solving and personal problem solving.

Later this experimental work continued through the 1960s and early 1970s with research conducted on relatively simple (but novel for participants) laboratory tasks of problem solving.[12][13] Choosing simple novel tasks was based on the clearly defined optimal solutions and their short time for solving, which made it possible for the researchers to trace participants' steps in problem-solving process.

Simon.[14] Other experts have shown that the principle of decomposition improves the ability of the problem solver to make good judgment.[15] In computer science and in the part of artificial intelligence that deals with algorithms ('algorithmics'), problem solving encompasses a number of techniques known as algorithms, heuristics, root cause analysis, etc.

In military science, problem solving is linked to the concept of 'end-states', the desired condition or situation that strategists wish to generate.[16]:xiii, E-2 The ability to solve problems is important at any military rank, but is highly critical at the command and control level, where it is strictly correlated to the deep understanding of qualitative and quantitative scenarios.

Effectiveness of problem solving is 'a criterion used to assess changes in system behavior, capability, or operational environment that is tied to measuring the attainment of an end state, achievement of an objective, or creation of an effect'.[16]:IV-24 Planning for problem-solving is a 'process that determines and describes how to employ 'means' in specific 'ways' to achieve 'ends' (the problem's solution).'[16]:IV-1 Forensic engineering is an important technique of failure analysis that involves tracing product defects and flaws.

Within the field of science there exists a set of fundamental standards, the scientific method, which outlines the process of discovering facts or truths about the world through unbiased consideration of all pertinent information and through impartial observation of and/or experimentation with that information.

Thus when one demonstrates confirmation bias, one is formally or informally collecting data and then subsequently observing and experimenting with that data in such a way that favors a preconceived notion that may or may not have motivation.[21] Research has found that professionals within scientific fields of study also experience confirmation bias.

Andreas Hergovich, Reinhard Schott, and Christoph Burger's experiment conducted online, for instance, suggested that professionals within the field of psychological research are likely to view scientific studies that are congruent with their preconceived understandings more favorably than studies that are incongruent with their established beliefs.[22] Motivation refers to one's desire to defend or find substantiation for beliefs (e.g., religious beliefs) that are important to one.[23] According to Raymond Nickerson, one can see the consequences of confirmation bias in real-life situations, which range in severity from inefficient government policies to genocide.

Thus research also shows that people can and do work to confirm theories or ideas that do not support or engage personally significant beliefs.[25] Mental set was first articulated by Abraham Luchins in the 1940s and demonstrated in his well-known water jug experiments.[26] In these experiments, participants were asked to fill one jug with a specific amount of water using only other jugs (typically three) with different maximum capacities as tools.

When people cling rigidly to their mental sets, they are said to be experiencing fixation, a seeming obsession or preoccupation with attempted strategies that are repeatedly unsuccessful.[28] In the late 1990s, researcher Jennifer Wiley worked to reveal that expertise can work to create a mental set in persons considered to be experts in certain fields, and she furthermore gained evidence that the mental set created by expertise could lead to the development of fixation.[28] Functional fixedness is a specific form of mental set and fixation, which was alluded to earlier in the Maier experiment, and furthermore it is another way in which cognitive bias can be seen throughout daily life.

In more technical terms, these researchers explained that '[s]ubjects become 'fixed' on the design function of the objects, and problem solving suffers relative to control conditions in which the object's function is not demonstrated.'[29] Functional fixedness is defined as only having that primary function of the object itself hinder the ability of it serving another purpose other than its original function.

In research that highlighted the primary reasons that young children are immune to functional fixedness, it was stated that 'functional fixedness...[is when]subjects are hindered in reaching the solution to a problem by their knowledge of an object's conventional function.'[30] Furthermore, it is important to note that functional fixedness can be easily expressed in commonplace situations.

Typically, the solver experiences this when attempting to use a method they have already experienced success from, and they can not help but try to make it work in the present circumstances as well, even if they see that it is counterproductive.[33] Groupthink, or taking on the mindset of the rest of the group members, can also act as an unnecessary constraint while trying to solve problems.[34] This is due to the fact that with everybody thinking the same thing, stopping on the same conclusions, and inhibiting themselves to think beyond this.

Standardized procedures like this can often bring mentally invented constraints of this kind,[35] and researchers have found a 0% correct solution rate in the time allotted for the task to be completed.[36] The imposed constraint inhibits the solver to think beyond the bounds of the dots.

Problems such as this are most typically solved via insight and can be very difficult for the subject depending on either how they have structured the problem in their minds, how they draw on their past experiences, and how much they juggle this information in their working memories[37] In the case of the nine-dot example, the solver has already been structured incorrectly in their minds because of the constraint that they have placed upon the solution.

These types of representations are often used to make difficult problems easier.[42] They can be used on tests as a strategy to remove Irrelevant Information, which is one of the most common forms of barriers when discussing the issues of problem solving.[33] Identifying crucial information presented in a problem and then being able to correctly identify its usefulness is essential.

Simon, 1977), researchers began to investigate problem solving separately in different natural knowledge domains – such as physics, writing, or chess playing – thus relinquishing their attempts to extract a global theory of problem solving (e.g.

In a 1962 research report, Douglas Engelbart linked collective intelligence to organizational effectiveness, and predicted that pro-actively 'augmenting human intellect' would yield a multiplier effect in group problem solving: 'Three people working together in this augmented mode [would] seem to be more than three times as effective in solving a complex problem as is one augmented person working alone'.[44] Henry Jenkins, a key theorist of new media and media convergence draws on the theory that collective intelligence can be attributed to media convergence and participatory culture.[45] He criticizes contemporary education for failing to incorporate online trends of collective problem solving into the classroom, stating 'whereas a collective intelligence community encourages ownership of work as a group, schools grade individuals'.

Jenkins argues that interaction within a knowledge community builds vital skills for young people, and teamwork through collective intelligence communities contribute to the development of such skills.[46] Collective impact is the commitment of a group of actors from different sectors to a common agenda for solving a specific social problem, using a structured form of collaboration.

As these global institutions remain state-like or state-centric it has been called unsurprising that these continue state-like or state-centric approaches to collective problem-solving rather than alternative ones.[47] Crowdsourcing is a process of accumulating the ideas, thoughts or information from many independent participants, with aim to find the best solution for a given challenge.

Integrating Learning Styles and Multiple Intelligences

Howard Gardner (1993) spells out the difference between the theories this way: In MI theory, I begin with a human organism that responds (or fails to respond) to different kinds of contents in the world.

45).We believe that the integration of learning styles and multiple intelligence theory may minimize their respective limitations and enhance their strengths, and we provide some practical suggestions for teachers to successfully integrate and apply learning styles and multiple intelligence theory in the classroom.

Learning-style theory begins with Carl Jung (1927), who noted major differences in the way people perceived (sensation versus intuition), the way they made decisions (logical thinking versus imaginative feelings), and how active or reflective they were while interacting (extroversion versus introversion).

Isabel Myers and Katherine Briggs (1977), who created the Myers-Briggs Type Indicator and founded the Association of Psychological Type, applied Jung's work and influenced a generation of researchers trying to understand specific differences in human learning.

Learning-style models tend to concern themselves with the process of learning: how individuals absorb information, think about information, and evaluate the results.

They recognize the role of cognitive and affective processes in learning and, therefore, can significantly deepen our insights into issues related to motivation.

They tend to emphasize thought as a vital component of learning, thereby avoiding reliance on basic and lower-level learning activities.

Emerging from a tradition that viewed style as relatively permanent, many learning-style advocates advised altering learning environments to match or challenge a learner's style.

The distinctions among these intelligences are supported by studies in child development, cognitive skills under conditions of brain damage, psychometrics, changes in cognition across history and within different cultures, and psychological transfer and generalization.

First, the theory has grown out of cognitive science—a discipline that has not yet asked itself why we have a field called cognitive science, but not one called affective science.

Perhaps one day, Gardner's work on the 'jagged profile' of combined intelligences or, perhaps, his insistence on the importance of context will produce a new understanding of intelligence.

The ability to use the body and tools to take effective action or to construct or repair.

The ability to use the body to build rapport, to console or persuade, and to support others.

The ability to plan strategically or to critique the actions of the body.

The ability to appreciate the aesthetics of the body and to use those values to create new forms of expression.

Working in this way, we devised a model that linked the process-centered approach of learning styles and the content and product-driven multiple intelligence theory.

Put together a magazine

Describe a complex procedure/object

Counsel a fictional character or a friend

Develop a plan to direct

Develop an advertising campaign

The following outline shows how we categorized abilities and sample vocations for the seven intelligences, by learning style: Linguistic

Mastery: The ability to use language to describe events and sequence activities (journalist, technical writer, administrator, contractor)

Understanding: The ability to use mathematical concepts to make conjectures, establish proofs, and apply mathematics and data to construct arguments (logician, computer programmer, scientist, quantitative problem solver)

Self-expressive: The ability to be sensitive to the patterns, symmetry, logic, and aesthetics of mathematics and to solve problems in design and modeling (composer, engineer, inventor, designer, qualitative problem solver)

Mastery: The ability to perceive and represent the visual-spatial world accurately (illustrator, artist, guide, photographer)

Interpersonal: The ability to arrange color, line, shape, form, and space to meet the needs of others (interior decorator, painter, clothing designer, weaver, builder)

Understanding: The ability to interpret and graphically represent visual or spatial ideas (architect, iconographer, computer graphics designer, art critic)

Self-expressive: The ability to transform visual or spatial ideas into imaginative and expressive creations (artist, inventor, model builder, cinematographer)

Mastery: The ability to use the body and tools to take effective action or to construct or repair (mechanic, trainer, contractor, craftsperson, tool and dye maker)

Interpersonal: The ability to use the body to build rapport, to console and persuade, and to support others (coach, counselor, salesperson, trainer)

Understanding: The ability to plan strategically or to critique the actions of the body (physical educator, sports analyst, professional athlete, dance critic)

Self-expressive: The ability to appreciate the aesthetics of the body and to use those values to create new forms of expression (sculptor, choreographer, actor, dancer, mime, puppeteer)

Mastery: The ability to understand and develop musical technique (technician, music teacher, instrument maker)

Interpersonal: The ability to respond emotionally to music and to work together to use music to meet the needs of others (choral, band, and orchestral performer or conductor;

Understanding: The ability to interpret musical forms and ideas (music critic, aficionado, music collector)

Interpersonal: The ability to use empathy to help others and to solve problems (social worker, doctor, nurse, therapist, teacher)

Understanding: The ability to discriminate and interpret among different kinds of interpersonal clues (sociologist, psychologist, psychotherapist, professor of psychology or sociology)

Self-expressive: The ability to influence and inspire others to work toward a common goal (consultant, charismatic leader, politician, evangelist)

Mastery: The ability to assess one's own strengths, weaknesses, talents, and interests and use them to set goals (planner, small business owner)

Self-expressive: The ability to reflect on one's inner moods, intuitions, and temperament and to use them to create or express a personal vision (artist, religious leader, writer)

For example, in the linguistic intelligence domain, a person with the Mastery style might write an article, put a magazine together, develop a newscast, or describe a complex procedure.

In conjunction, both multiple intelligences and learning styles can work together to form a powerful and integrated model of human intelligence and learning—a model that respects and celebrates diversity and provides us with the tools to meet high standards.

Problem-based learning

Wood (2003) defines problem-based learning as a process that uses identified issues within a scenario to increase knowledge and understanding.[1] The principles of this process are listed below: The PBL process was pioneered by Barrows and Tamblyn at the medical school program at McMaster University in Hamilton in the 1960s.[4] Traditional medical education disenchanted students, who perceived the vast amount of material presented in the first three years of medical school as having little relevance to the practice of medicine and clinically based medicine.[4] The PBL curriculum was developed in order to stimulate learning by allowing students to see the relevance and application to future roles.

Problem-based learning has subsequently been adopted by other medical school programs[4] adapted for undergraduate instruction,[5][6][7] as well as K-12.[4][8] The use of PBL has expanded from its initial introduction into medical school programs to include education in the areas of other health sciences, math, law, education, economics, business, social studies, and engineering.[8] PBL includes problems that can be solved in many different ways depending on the initial identification of the problem and may have more than one solution.[9] There are advantages of PBL.

It also helps to develop life skills that are applicable to many domains.[10] It can be used to enhance content knowledge while simultaneously fostering the development of communication, problem-solving, critical thinking, collaboration, and self-directed learning skills.[11][12] PBL may position students to optimally function using real-world experiences.

It encourages self-directed learning by confronting students with problems and stimulates the development of deep learning.[14] Problem-based learning gives emphasis to lifelong learning by developing in students the potential to determine their own goals, locate appropriate resources for learning and assume responsibility for what they need to know.[15] (Candy PC.

When students are given more challenging and significant problems are given it makes them more proficient.[19] The real life contexts and problems makes their learning more profound, lasting and also enhance the transferability of skills and knowledge from the classroom to work.[20] Since there is more scope for application of knowledge and skills the transferability is increased.

The teams or groups resolve relevant problems in collaboration and hence it fosters student interaction, teamwork and reinforces interpersonal skills.[22] like peer evaluation, working with group dynamic etc.[23] It also fosters in them the leadership qualities, learn to make decision by consensus and give constructive feed back to the team members etc.[24] Researchers say that students like problem-based learning classes rather than the traditional classes.

the teachers who have worked in both traditional and project based learning formats prefer project based learning.[26] They also feel that problem-based learning is more nurturing, significant curriculum and beneficial to the cognitive growth of the student.[19] The PBL students score higher than the students in traditional courses because of their learning competencies, problem solving, self-assessment techniques, data gathering, behavioral science etc.[27] It is because they are better at activating prior knowledge, and they learn in a context resembling their future context and elaborate more on the information presented which helps in better understanding and retention of knowledge.[28] In medical education, PBL cases can incorporate dialogue between patients and physicians, demonstrate the narrative character of the medical encounter, and examine the political economic contributors to disease production.

Students may not have access to teachers who serve as the inspirational role models that traditional curriculum offers.[30] Although students generally like and gain greater ability to solve real-life problems in problem-based learning courses, instructors of the methodology must often invest more time to assess student learning and prepare course materials, as compared to LBL instructors.[26] Part of this frustration also stems from the amount of time dedicated to presenting new research and individual student findings regarding each specific topic, as well as the disorganised nature of brain-storming[31] The problem of the problem-based learning is the traditional assumptions of the students.

Problem-based has also been considered more favourable to female participants,[33] whilst having equivocal impacts on their male counterparts when compared to lecture based learning.[34] Sweller and others published a series of studies over the past twenty years that is relevant to problem-based learning, concerning cognitive load and what they describe as the guidance-fading effect.[35] Sweller et al.

Implementing PBL in schools and Universities is a demanding process that requires resources, a lot of planning and organization.[42] Azer discusses the 12 steps for implementing the 'pure PBL'[42] Problem-based learning addresses the need to promote lifelong learning through the process of inquiry and constructivist learning.[2] PBL is considered a constructivist approach to instruction because it emphasizes collaborative and self-directed learning while being supported by tutor facilitation.[43] Yew and Schmidt,[44] Schmidt, and Hung elaborate on the cognitive constructivist process of PBL:[2][3] PBL follows a constructivist perspective in learning as the role of the instructor is to guide and challenge the learning process rather than strictly providing knowledge.[45][46] From this perspective, feedback and reflection on the learning process and group dynamics are essential components of PBL.

PBL assists in processes of creating meaning and building personal interpretations of the world based on experiences and interactions.[47] PBL assists to guide the student from theory to practice during their journey through solving the problem.[48] Several studies support the success of the constructivist problem-based and inquiry learning methods.[49] One example is a study on a project called GenScope, an inquiry-based science software application, which found that students using the GenScope software showed significant gains over the control groups, with the largest gains shown in students from basic courses.[49] One large study tracked middle school students' performance on high-stakes standardized tests to evaluate the effectiveness of inquiry-based science.[49] The study found a 14 percent improvement for the first cohort of students and a 13 percent improvement for the second cohort.[49] The study also found that inquiry-based teaching methods greatly reduced the achievement gap for African-American students.[49] A

In Universiti Malaya, the Bachelor of Medicine, Bachelor of Surgery and Bachelor of Dental Surgery courses included several sessions of problem-based learning in their curriculum as a way of teaching interactions between students.[citation needed] In Singapore, the most notable example of adopting PBL pedagogy in curriculum is Republic Polytechnic, the first polytechnic in Singapore to fully adopt PBL across all diploma courses.[citation needed] Several medical schools have incorporated problem-based learning into their curricula following the lead of McMaster University Medical School, using real patient cases to teach students how to think like a clinician.

More than eighty percent of medical schools in the United States now have some form of problem-based learning in their programs.[52] Research of 10 years of data from the University of Missouri School of Medicine indicates that PBL has a positive effect on the students' competency as physicians after graduation.[50] Monash University was the second institution to adopt PBL within a medical school environment and continues to apply this within the Faculty of Medicine, Nursing and Health Sciences for the Bachelor of Medicine / Bachelor of Surgery (MBBS) programs delivered in Australia and Malaysia.[citation needed] Maastricht University offers its whole program in PBL format only, as does St. George's University of London, another pioneer in the PBL format.

Rikers' discussion, SDL is defined as 'a process in which individuals take the diagnosing their learning needs, formulating goals, identifying human and material resources, choosing and implementing appropriate learning strategies, and evaluating learning outcomes'.[59] By being invited into the learning process, students are also invited to take responsibility for their learning, which leads to an increase in self-directed learning skills.

In Severiens and Schmidt's study of 305 first year college students, they found that PBL and its focus on SDL led to motivation for students to maintain study pace, led to social and academic integration, encouraged development of cognitive skills, and fostered more study progress than students in a conventional learning setting.[60] PBL encourages learners to take a place in the academic world through inquiring and discovery that is central to problem-based learning.

PBL is also argued as a learning method that can promote the development of critical thinking skills.[61] In PBL learning, students learn how to analyze a problem, identify relevant facts and generate hypotheses, identify necessary information/knowledge for solving the problem and make reasonable judgments about solving the problem.

Online PBL is also seen as more cost-effective.[63] Collaborative PBL has been shown to improve critical thinking scores as compared with individual PBL, and increased students’ achievement levels and retention scores.[64] For the instructors, instructional design principles for the instructors regarding the design and development of online PBL must include collaborative characteristics.

The result showed the significant impact of online PBL on the learning outcomes of students in many aspects including enhancing their communication skills, problem-solving skills and ability to work as a team.[65] The most successful feature of the LMS in terms of user rate was the discussion boards where asynchronous communications took place.

Educators of all kinds (K-12 schools, colleges, and universities, vocational training, HR training teams, etc.) can access these cloud-based solutions and collaborate with anyone around the world by simply sharing a link.[66] These tools range in availability from free with an email account to subscription costs based on the suit purchased.

[68] The third most important phase of PBL is resolving the problem, the critical task is presenting and defending your solution to the given problem.[69] Students need to be able to state the problem clearly, describe the process of problem-solving considering different options to overcome difficulties, support the solution using relevant information and data analysis.[70] Being able to communicate and present the solution clearly is the key to the success of this phase as it directly affects the learning outcomes.

The P5BL approach was a learning strategy introduced in Stanford School of Engineering in their P5BL laboratory in 1993 as an initiative to offer their graduate students from the engineering, architecture and construction disciplines to implement their skills in a 'cross-disciplinary, collaborative and geographically distributed teamwork experience'.[73] In this approach, which was pioneered by Stanford Professor Fruchter, an environment across six universities from Europe, the United States and Japan along with a toolkit to capture and share project knowledge was developed.[74] The students (people) from the three disciplines were assigned a team project that works on solving a problem and delivering an end-product to a client.

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