scholarly journals Deterministic response strategies in trial-and-error learning

2018 ◽  
Author(s):  
Holger Mohr ◽  
Katharina Zwosta ◽  
Dimitrije Markovic ◽  
Sebastian Bitzer ◽  
Uta Wolfensteller ◽  
...  
Keyword(s):  
Learning Strategies ◽  
Cognitive Processes ◽  
Learning Model ◽  
Trial And Error ◽  
Q Learning ◽  
Learning Efficiency ◽  
Stimulus Response ◽  
Initial Learning ◽  
Error Learning ◽  
High Level

Trial-and-error learning is a universal strategy for establishing which actions are beneficial or harmful in new environments. However, learning stimulus-response associations solely via trial-and-error is often suboptimal, as in many settings dependencies among stimuli and responses can be exploited to increase learning efficiency. Previous studies have shown that in settings featuring such dependencies, humans typically engage high-level cognitive processes and employ advanced learning strategies to improve their learning efficiency. Here we analyze in detail the initial learning phase of a sample of human subjects (N = 85) performing a trial-and-error learning task with deterministic feedback and hidden stimulus-response dependencies. Using computational modeling, we find that the standard Q-learning model cannot sufficiently explain human learning strategies in this setting. Instead, newly introduced deterministic response models, which are theoretically optimal and transform stimulus sequences unambiguously into response sequences, provide the best explanation for 50.6% of the subjects. Most of the remaining subjects either show a tendency towards generic optimal learning (21.2%) or at least partially exploit stimulus-response dependencies (22.3%), while a few subjects (5.9%) show no clear preference for any of the employed models. After the initial learning phase, asymptotic learning performance during the subsequent practice phase is best explained by the standard Q-learning model. Our results show that human learning strategies in trial-and-error learning go beyond merely associating stimuli and responses via incremental reinforcement. Specifically during initial learning, high-level cognitive processes support sophisticated learning strategies that increase learning efficiency while keeping memory demands and computational efforts bounded. The good asymptotic fit of the Q-learning model indicates that these cognitive processes are successively replaced by the formation of stimulus-response associations over the course of learning.

Learning, Transfer, and Retention of Errorless Fading versus Trial-and-Error Teaching

1978 ◽  
Vol 43 (2) ◽  
pp. 553-554 ◽  
Author(s):  
William D. Ellis ◽  
Barbara L. Ludlow ◽  
Richard T. Walls
Keyword(s):  
Discrimination Task ◽  
Learning Transfer ◽  
Trial And Error ◽  
Line Drawings ◽  
Initial Learning ◽  
Fourth Grade Students ◽  
Transfer And Retention ◽  
History Of ◽  
Error Learning ◽  
Versus Trial

Although several investigators have used prompting and fading techniques to teach tasks with few or no errors, there has been disagreement about subsequent transfer and retention as compared with trial-and-error learning. Fourth grade students in an errorless fading condition learned a symbol discrimination task by a prompting and fading program in which relevant characteristics of the line drawings were emphasized. Another group learned the same discrimination by trial-and-error with right-and-wrong feedback. Findings indicated that percentage of errors was less for errorless fading than trial-and-error in initial learning but did not differ during transfer or retention. However, in terms of time, a history of prompting-fading learning did not transfer to trial-and-error learning as well as one of trial-and-error learning.

scholarly journals Problem Solving in Animals: Proposal for an Ontogenetic Perspective

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 866
Author(s):  
Misha K. Rowell ◽  
Neville Pillay ◽  
Tasmin L. Rymer
Keyword(s):  
Problem Solving ◽  
Environmental Factors ◽  
Cognitive Processes ◽  
Current Literature ◽  
Experimental Studies ◽  
Trial And Error ◽  
Full Understanding ◽  
Comprehensive Review ◽  
Ultimate Outcome ◽  
Error Learning

Problem solving, the act of overcoming an obstacle to obtain an incentive, has been studied in a wide variety of taxa, and is often based on simple strategies such as trial-and-error learning, instead of higher-order cognitive processes, such as insight. There are large variations in problem solving abilities between species, populations and individuals, and this variation could arise due to differences in development, and other intrinsic (genetic, neuroendocrine and aging) and extrinsic (environmental) factors. However, experimental studies investigating the ontogeny of problem solving are lacking. Here, we provide a comprehensive review of problem solving from an ontogenetic perspective. The focus is to highlight aspects of problem solving that have been overlooked in the current literature, and highlight why developmental influences of problem-solving ability are particularly important avenues for future investigation. We argue that the ultimate outcome of solving a problem is underpinned by interacting cognitive, physiological and behavioural components, all of which are affected by ontogenetic factors. We emphasise that, due to the large number of confounding ontogenetic influences, an individual-centric approach is important for a full understanding of the development of problem solving.

PELAKSANAAN MODEL PEMBELAJARAN KOOPERATIF TIPE STAD UNTUK MENINGKATKAN HASIL BELAJAR PPKn SISWA SMP NEGERI 3 TELUK KUANTAN

2018 ◽  
Vol 2 (5) ◽  
pp. 789
Author(s):  
Maria Yulianti
Keyword(s):  
Cooperative Learning ◽  
Initial Data ◽  
Student Learning ◽  
Learning Outcomes ◽  
Student Learning Outcomes ◽  
Learning Model ◽  
Learning Models ◽  
The Subject ◽  
High Level

The background of this study was the low student learning outcomes of PPKn, from 28 students who achievedthe completeness criteria at least only 11 students (39.29%). The low student learning outcomes are caused bythe high level of individuality between students so that the achievement of competence among studentsexperiences a very distant difference. Based on this, the researchers made improvements to student learningoutcomes through the application of STAD cooperative learning models. This research is a classroom actionresearch, with the subject of class VII of SMP Negeri 3 Teluk Kuantan. The data used in this study is PPKnlearning outcomes data. The results stated that after applying the STAD type cooperative learning model studentlearning outcomes had increased in the initial data the number of students who completed were 11 students, incycle I had an increase with the number of 18 students, and in cycle II the number of students who completedcontinued to increase by the number 22 student.

MODIFIKASI MODEL PEMBELAJARAN TEAM ASSISTED INDIVIDUALIZATION DENGAN STRATEGI PEMBELAJARAN TUGAS DAN PAKSA

2019 ◽  
Vol 2 ◽  
Author(s):  
Lea Christy Restu Kinasih ◽  
Dewi Fatimah ◽  
Veranica Julianti
Keyword(s):  
Cooperative Learning ◽  
Learning Strategies ◽  
Learning Process ◽  
Learning Model ◽  
Learning Models ◽  
Classroom Learning ◽  
Quality Of Learning ◽  
The Given

The selection and determination of appropriate learning strategies can improve the results to be obtained from the application of classroom learning models. This writing aims to discipline students to develop individual abilities of students to be more active in the learning process and improve the quality of learning. The learning process in Indonesia in general only uses conventional learning models that make students passive and undeveloped. In order for the quality of learning to increase, the Team Assisted Individualization learning model is combined with the task learning and forced strategies. The Team Assisted Individualization cooperative learning model is one of the cooperative learning models that combines learning individually and in groups. Meanwhile, task and forced learning strategies are strategies that focus on giving assignments that require students to complete them on time so that the learning process can run effectively. Students are required to do assignments according to the given deadline. This makes students become familiar with the tasks given by the teacher. Combining or modifying the learning model of the assisted individualization team with forced and forced learning strategies is expected to be able to make students more active, disciplined, independent, creative in learning and responsible for the tasks assigned. Therefore this method of incorporation is very necessary in the learning process and can be applied to improve the quality of learning in schools.

Modifikasi Model Pembelajaran Problem Based Learning (PBL) dengan Strategi Pembelajaran Tugas dan Paksa

2019 ◽  
Vol 2 ◽  
Author(s):  
Tita Mila Mustofani ◽  
Ita Hartinah
Keyword(s):  
Critical Thinking ◽  
Learning Strategies ◽  
Student Motivation ◽  
Problem Based Learning ◽  
Learning Model ◽  
Learning Material ◽  
Task Strategies ◽  
The Right ◽  
Increasing Student Learning

This writing aims to help teachers to increase motivation, activity, creativity, and critical thinking of students in solving problems in class. The way to increase student motivation in learning in class is to choose the right learning model with ongoing learning material. One learning model that increases students' creativity and critical thinking in problem solving is a Problem Based Learning (PBL) learning model. To improve students' insights in order to easily solve problems there is a need to do tasks, if students do not do the task then they must accept the agreed upon consequences when making learning contracts, thus modifying the Problem Based Learning (PBL) learning model with task strategies and forced. The results of the modification of learning with the Problem Based Learning (PBL) learning model through forced and forced strategies are expected to improve the learning process so that students become more disciplined and do not waste time doing assignments. The advantages of modifying the Problem Based Learning (PBL) learning model with task and forced learning strategies are increasing student learning motivation, improving the quality of learning, training students' understanding by giving assignments continuously, teaching discipline to students in order to be accountable for tasks assigned, and reducing laziness in students.

Focused Tasks, Mental Actions and Second Language Learning. Cognitive and Connectionist Accounts of Task Effectiveness

2006 ◽  
Vol 152 ◽  
pp. 35-53 ◽  
Author(s):  
Machteld Moonen ◽  
Rick de Graaff ◽  
Gerard Westhoff
Keyword(s):  
Second Language ◽  
Language Learning ◽  
Learning Strategies ◽  
Cognitive Processes ◽  
Second Language Learning ◽  
Theoretical Framework ◽  
Future Research ◽  
Depth Of Processing ◽  
Mental Actions ◽  
Involvement Load Hypothesis

Abstract This paper presents a theoretical framework to estimate the effectiveness of second language tasks in which the focus is on the acquisition of new linguistic items, such as vocabulary or grammar, the so-called focused tasks (R. Ellis, 2003). What accounts for the learning impact offocused tasks? We shall argue that the task-based approach (e.g. Skehan, 1998, Robinson, 2001) does not provide an in-depth account of how cognitive processes, elicited by a task, foster the acquisition of new linguistic elements. We shall then review the typologies of cognitive processes derived from research on learning strategies (Chamot & O'Malley, 1994), from the involvement load hypothesis (Laufer & Hulstijn, 2001), from the depth of processing hypothesis (Craik & Lockhart, 1972) and from connectionism (e.g Broeder & Plunkett, 1997; N. Ellis, 2003). The combined insights of these typologies form the basis of the multi-feature hypothesis, which predicts that retention and ease of activation of new linguistic items are improved by mental actions which involve a wide variety of different features, simultaneously and frequently. A number of implications for future research shall be discussed.

scholarly journals Deep Q-Learning for Two-Hop Communications of Drone Base Stations

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1960
Author(s):  
Azade Fotouhi ◽  
Ming Ding ◽  
Mahbub Hassan
Keyword(s):  
Degrees Of Freedom ◽  
Network Performance ◽  
Learning Model ◽  
Base Stations ◽  
Communication Model ◽  
Complex Environments ◽  
End User ◽  
Q Learning ◽  
Trajectory Simulation ◽  
Target Environment

In this paper, we address the application of the flying Drone Base Stations (DBS) in order to improve the network performance. Given the high degrees of freedom of a DBS, it can change its position and adapt its trajectory according to the users movements and the target environment. A two-hop communication model, between an end-user and a macrocell through a DBS, is studied in this work. We propose Q-learning and Deep Q-learning based solutions to optimize the drone’s trajectory. Simulation results show that, by employing our proposed models, the drone can autonomously fly and adapts its mobility according to the users’ movements. Additionally, the Deep Q-learning model outperforms the Q-learning model and can be applied in more complex environments.

Sign in / Sign up

Export Citation Format

Share Document