search algorithms constitute an important topic in the Artificial Intelligence curriculum and are acknowledged by most tutors to be a hard and complex domain for teachers to teach and students to deeply understand. In...
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ISBN:
(纸本)9789897581793
search algorithms constitute an important topic in the Artificial Intelligence curriculum and are acknowledged by most tutors to be a hard and complex domain for teachers to teach and students to deeply understand. In this paper, we present an educational computer game, designed to teach search algorithms, based on the popular Pacman game. The purpose of the educational Pacman game is to assist students to understand the artificial intelligence topic of search algorithms in an entertaining, interactive and motivating way. During their experience with the game, students can examine the behaviour of various search algorithms and a graphical annotated depiction of them through suitable visualizations. Visualizations can demonstrate the operational functionality of algorithms and are designed in line with the principles of student's active learning. Various learning activities were designed and request students to apply specific search algorithms in various example cases with or without the assistance and feedback of the game. An evaluation study was conducted in real classroom conditions and revealed quite satisfactory results. The results indicate that the educational Pacman game is an effective way to enhance students' engagement and help them to deeper understand the AI search algorithms.
We have developed and use in our Department the Artificial Intelligence Teaching System (AITS). AITS is an adaptive and intelligent tutoring system that teaches AI aspects and uses AI techniques for personalized learn...
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ISBN:
(纸本)9781479966004
We have developed and use in our Department the Artificial Intelligence Teaching System (AITS). AITS is an adaptive and intelligent tutoring system that teaches AI aspects and uses AI techniques for personalized learning and assessment of the students. In this paper, we present the way that AITS can help students in learning search algorithms and the learning approaches and activities it offers. Also, we present a tool developed to assist tutors to create exercises in a semi- automatic way. It is an assistant tool to be embedded into the AITS system that produces different types of interactive exercises related to AI search algorithms. The tool takes as input a number of parameters regarding the desired exercise and it creates semiautomatically the interactive exercise based on the corresponding parameters. The tool aims at helping tutors in creating and updating the teaching material. Results gathered from an evaluation study are quite promising.
In our investigation we focus on the A* Algorithm, for solving path-finding problems, because it is fairly flexible and can be used in a wide range of contexts. The main problem of A* Algorithm is the finite computer ...
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ISBN:
(纸本)9788363578015
In our investigation we focus on the A* Algorithm, for solving path-finding problems, because it is fairly flexible and can be used in a wide range of contexts. The main problem of A* Algorithm is the finite computer memory. Using this method, the robot can decide how to move from end to end point in an efficient manner without colliding with previously mapped obstacles. When in need of finding a path on considerably large map, computer has to remember a complex list of examined and open nodes, which can occupy most of free space in computer memory. Nonetheless, this solution shows the best results and it is worth analyzing as the algorithm for the intelligent robot movements.
Feedback constitutes a fundamental aspect of educational systems that has a substantial impact on students learning and can shape their mental models. The delivery of appropriate feedback in terms of time and content ...
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ISBN:
(数字)9783319676159
ISBN:
(纸本)9783319676159;9783319676142
Feedback constitutes a fundamental aspect of educational systems that has a substantial impact on students learning and can shape their mental models. The delivery of appropriate feedback in terms of time and content is crucial for facilitating students' knowledge construction and comprehension. In this paper, we examine the complex nature and the efficiency of feedback in the context of a virtual reality educational environment. More specifically, we study the effect that different types of feedback such as feedback with visualized animations of procedures, can have on students learning and knowledge construction in a virtual reality educational environment for learning blind and heuristic search algorithms. An experimental study was designed where participating students were engaged with learning activities and solved exercises in different feedback conditions. Results from the study indicate that visual types of feedback can have a substantial impact on students' learning, assisting them in better understanding the functionality of the process studied with respect to performance and mistakes.
Quantum Computers are not limited to just two states. Qubits, the basic unit of quantum computing have the power to exist in more than one state at a time. While the classical computers only perform operations by mani...
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ISBN:
(纸本)9783030325206;9783030325190
Quantum Computers are not limited to just two states. Qubits, the basic unit of quantum computing have the power to exist in more than one state at a time. While the classical computers only perform operations by manipulation of classical bits having two values 0 and 1, quantum bits can represent data in multiple states. This property of inheriting multiple states at a time is called superposition which gives quantum computers tremendous power over classical computers. With this power, the algorithms designed on quantum computers to solve search queries can yield result significantly faster than the classical algorithms. There are four types of problems that exist: Polynomial (P), Non-Deterministic Polynomial (NP), Non-Deterministic Polynomial Complete (NP-complete) and Non-Deterministic Polynomial hard (NP-hard). P problems can be solved in the polynomial amount of time like searching a database for an item. However, when the size of the search space grows, it becomes difficult to compute solutions even for P problems. Quantum algorithms like Grover's algorithm has reduced the tvime complexity of some of the classical algorithm problems from N to root N. Variants of Grover's algorithm like Quantum Partial search propose changes that yield not exact but closer results in time even lesser than Grover's algorithm. NP problems are the problems whose solution if known can be verified in polynomial amount time. Factorization of prime numbers which is considered to be an NP problem took an exponential amount of time when solved using the classical computer while the Shor's quantum computing algorithm computes it in polynomial time. Factorization is also a class of bounded-error quantum polynomial time (BQP) problems which are decision problems solved by quantum computers in polynomial time. There are problems to which if a solution is found can solve every problem Of NP class, these are NP-complete problems. The power of Qubits could be exploited in the future to come up
Automated program repair (APR) techniques locate and fix faults automatically. In order to fix faults, APR applies a set of program modification operators (PMOs) to modify faulty programs. A potential repair is found ...
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Automated program repair (APR) techniques locate and fix faults automatically. In order to fix faults, APR applies a set of program modification operators (PMOs) to modify faulty programs. A potential repair is found when APR applies a PMO that fixes a fault. A brute-force search algorithm applies all PMOs in a predefined order until a potential repair is found. Brute-force can guarantee a fix but lowers APR performance, especially when it uses many PMOs. Stochastic search algorithms, such as a genetic algorithm, efficiently search the modifications space for a PMO that fixes a fault. In this paper, we conduct a comprehensive evaluation of the impact on APR effectiveness, APR performance, and the quality of potential repairs of three stochastic search algorithms:(1) a genetic algorithm (GA), (2) a genetic algorithm without a crossover operator (GAWoCross), and (3) a random search (RS). Our evaluation using 41 faulty versions of six different C programs shows that RS improves APR effectiveness and performance, but GA and GAWoCross improve the quality of potential repairs by generating more validated repairs, and potential repairs that failed fewer regression tests compared to RS. (C) 2015 Published by Elsevier B.V.
Earth Observation (EO) through remote sensing satellites gathers reliable information about the environment. The evolution of satellite instrumentation leads to considerable satellite data volumes which require on one...
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ISBN:
(纸本)9781538670422
Earth Observation (EO) through remote sensing satellites gathers reliable information about the environment. The evolution of satellite instrumentation leads to considerable satellite data volumes which require on one hand, mathematically and statistically based algorithms to extract valuable information and, on the other hand, increased computational power for processing. The paper proposes image processing algorithms for Synthetic Aperture Radar (SAR) images together with application-specific hardware architectures for satellite imagery. It is well known that performing feature extraction in image analysis involves complex search algorithms implementation. A novel approach based on content-addressable memories (CAM) for search algorithms optimization is proposed. Results in terms of computational time are presented for the proposed approach and compared with classical image processing search algorithms implementations.
Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions, potential high loss rate and the decentralized architecture. To support long and high-quality streams, on...
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ISBN:
(纸本)9783540725893
Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions, potential high loss rate and the decentralized architecture. To support long and high-quality streams, one viable approach is that a media stream is partitioned into segments, and then the segments are replicated in a network and served in a peer-to-peer fashion, however, the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ant-inspired search algorithm (HASA) for P2P media streaming distribution in Ad Hoc networks. It takes the advantages of random walkers and ant-inspired algorithms for search in unstructured P2P networks, such as low transmitting latency and less redundant query messages. We quantify the performance of our scheme in terms of response time and network query messages for media streaming distribution. Simulation results show that it can effectively improve the search Efficiency for P2P media streaming distribution in Ad Hoc networks.
Although chess seems like a simple game, considering the quick learning of movements of the chess pieces and other rules, when a solution space is formed for movement possibilities by speculating future movements, com...
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ISBN:
(纸本)9781509016792
Although chess seems like a simple game, considering the quick learning of movements of the chess pieces and other rules, when a solution space is formed for movement possibilities by speculating future movements, complexity and strategic aspects of the game can be better understood. In this study, heuristic methods are utilized in order to search for deeper solutions in the chess game. This way, a person's or standard search algorithms' difficulty in scanning through movements which could amount to millions is tried to be surpassed by heuristic methods. Heuristic methods, rather than scanning the whole space, focus on promising areas and look for the best solution. The results gained from experimental studies reveal the possibility of making a deeper search, while emphasizing the advantages of using heuristic methods as a searching method in chess.
Cyber-Physical Systems (CPSs) can be found in many sectors (e.g., automotive and aerospace). These systems are usually configurable to give solutions based on different needs. The variability of these systems is large...
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ISBN:
(纸本)9781450342063
Cyber-Physical Systems (CPSs) can be found in many sectors (e.g., automotive and aerospace). These systems are usually configurable to give solutions based on different needs. The variability of these systems is large, which implies they can be set into millions of configurations. As a result, different testing processes are needed to efficiently test these systems: the appropriate configurations must be selected and relevant test cases for each configuration must be chosen as well as prioritized. Prioritizing the order in which the test cases are executed reduces the time for detecting faults in these kinds of systems. However, the test suite size is often large and exploring all the possible test case orders is infeasible. search algorithms can help find optimal solutions from a large solution space. This paper presents an approach based on weight-based search algorithms for prioritizing the test cases for configurable CPSs. We empirically evaluate the performance of the following algorithms with two case studies: Weight-Based Genetic algorithms, Random Weighted Genetic algorithms, Greedy, Alternating Variable Method and Random search (RS). Our results suggest that all the search algorithms outperform RS, which is taken as a baseline. Local search algorithms have shown better performance than global search algorithms.
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