COMP3004程序写作、辅导c++，Python

” COMP3004程序写作、辅导c++，PythonCOMP3004/COMP4105Designing Intelligent AgentsCourseworkColin JohnsonOverviewThe coursework for this module is based Around you designing intelligent autonomousagents and an environment with which they interact, setting those agents a task, asking oneor more questions about that task, and evaluating it using experimental methods. You willthen present the results from this in a report, which will also explain the context for the work. DetailsAn autonomous intelligent agent is a Program that operates in a particular environment, perceives aspects of that environment, and then carries out actions that change thatenvironment to carry out some task. Typically, these actions are a mixture of responses to itsperception and proactive actions such as exploration. Your task for this coursework is to design an agent-based system containing the followingfour aspects:An Environment. This is the (virtual) place where the agents will operate. It could be one of: A simulation of a physical environment in which mobile robotic agents move. Thiscould be the simulation used in the classes earlier in the semester (perhapsextended), a robot environment such as The Player Project( https://playerstage.sourceforge.net), or a project in Unity or a similar gameenvironment if you are familiar with one from elsewhere. A chatbot environment such as the ones used in the classes. The blackboard system used in the class where we discussed language agentswriting poetry The Bristol Stock Exchange system introduced in the classes later in the semester( httpss://github.com/davecliff/BristolStockExchange) or a similar simulation of someaspect of the economy or society A game environment such as Ms. PacMan ( httpss://gym.openai.com/envs/MsPacman- v0/), the Open Racing Car Simulator ( https://torcs.sourceforge.net), RoboCup( httpss://www.robocup.org/leagues/23) or similar (see e.g. https://www.gvgai.net) One of the more complex task environments from the OpenAI Gym( httpss://gym.openai.com)There is no need to develop the environment yourselfthe focus of the project will be on theagents in the environment (chatbots, robots, trading agents, game-playing agents, autonomous drivers, etc.) but it is likely that you will set up the details of the environmentto address your specific question. You are allowed to use the code from the classes, butplease try to make it clear broadly which parts of the code are taken from the class examples, and which is your own work (we appreciate that this is sometimes complicated to do at aline-by-line level, but you should indicate this in broad terms). Autonomous Agents. You should introduce one or more autonomous agents into theenvironment, which use some kind of AI to solve a task. Examples of AI could be an AI planning system such as Goal Oriented ActionPlanning ( https://alumni.media.mit.edu/~jorkin/goap.html), a search algorithm such asA* search, a genetic or swarm search, a reinforcement learning algorithm, fuzzy logic, or a hard-coded reactive or state-machine AI. The task will be one relevant to the environment: e.g. a robot vacuum cleanerclearing up dirt, a chatbot taking an order From a customer, a trader trying to optimiseits returns, a game player trying to get a high score in a game, etc. Within reason, you can use any language to do this. If you are planning to use anythingother than Python, Java, Matlab/Octave, JavaScript, and standard web technologies such asHTML/CSS, then please mention this in your topic approval. A Question. You should be asking a specific question (or a set of related questions) aboutyour system. For example: How do different approaches (a genetic algorithm, an A* search algorithm, a hard- coded heuristic) compare in terms of task performance? How does the performance of the system change as we vary the number of agents init? If the system is trained on one version of the environment, does that learning transferover to a new version of the environment How do different kinds of communication/coordination between agents effect theefficiency of those agents on the task How much improvement does storing some information (e.g. a map of theenvironment) make compared to carrying out the task in a purely reactive way? How do different kinds of sensing/perception systems affect the capacity of the agentto carry out its task? How sensitive is the agent to error/noise?A Set of Experiments. You should answer your question by carrying out a set of experiments. Remember the structure that we talked about in one of the lectures: implement code that carries out a run of the agents behaviour and measuresperformance then, run that code multiple times to get a measure of average performance then, repeat that process for the different conditions in your question, and usedescriptive statistics, charts/visualisation, and/or inferential statistics (e.g. significance tests) to test your questionThen, you are in a position to discuss the question using these experimental results as yourevidence. ExamplesHere are a few examples of things that you could do. You dont have to do one of theseindeed, we would prefer you to come up with your own ideabut, these would all beacceptable project ideas if you want to do them: To take the robot vacuum cleaner from the early classes, and experiment withdifferent numbers of robots, and different coordination strategies (e.g. robots try tostay a fixed distance from each other, compared to sharing a map that they build up) Contrast random, fixed and planned orders of asking questions in a chatbot, and see(perhaps by doing a brief user test) which one is better. Take a number of different trading strategies and run them in the Bristol StockExchange system with varying amounts of noise/uncertainty, to see how robust eachstrategy is. Take the avoid the cats problem from the class, and compare a number ofstrategies for the problem: warning the cats vs. moving out of the way, and learningwhen to act based on a simple statistical approach vs. a decision-tree approach. Consider the problem of planning a robots movement around a mapped environment(e.g. the map generated from WiFi triangulation introduced in one of the classes). Contrast A* search and genetic algorithms on this problem, and compare them bothagainst random wandering. Topic ApprovalYou should submit a short description of your project idea (around a paragraph, 100 word)on the Moodle page by 15:00 on the 7th May 2021. We will then give you feedback onwhether the project is an acceptable one, and how it might be modified or improved. You donot have to wait until then before submitting your idea; we will start looking at them from mid- April onwards. SubmissionBy 3pm on 18th June 2021 should submit the following. This may be extended if you have asupport plan or extenuating circumstances. Late submissions will incur a penalty of 5% perworking day, up to 25th June 2021, after which you will receive a mark of zero. COMP3004A report, around 2500 words (a little longer if you need it), where you describe: The core ideas of your project; clearly state the question that you are trying to answer A review of relevant ideas, technologies and research papers How you designed the environment and agents in order to address that question Technologies used, and challenges that you met in doing the implementation How you set up and ran your experiments The results from your experiments A discussion of the question in light of The experimental results A conclusion, where you summarise the work, reflect on its successes and limitations, and briefly mention some ideas for how you would take the work forward if you hadmore timeA copy of your code, either as an upload or a link to a repositoryAnything else that you think would be helpful for the markers, e.g. sample outputs from yoursystem, a link to a brief video demonstrating it working, etc. COMP4105A report, around 2000 words (a little longer if you need it), where you describe: The core ideas of your project; clearly state the question that you are trying to answer How you designed the environment and agents in order to address that question Technologies used, and challenges that you met in doing the implementation How you set up and ran your experiments The results from your experiments A discussion of the question in light of the experimental results A conclusion, where you summarise the work, reflect on its successes and limitations, and briefly mention some ideas for how you would take the work forward if you hadmore timeA report, about 1500-2000 words, where you give an extended review of relevant ideas,technologies and research papersA 10-minute presentation about your work (dates/times will be arranged)A copy of your code, either as an upload or a link to a repositoryAnything else that you think would be helpful for the markers, e.g. sample outputs from yoursystem, a link to a brief video demonstrating it working, etc. Academic IntegrityThis is an individual assessment that should consist of your own unaided work. You shouldmake any direct quotations clear both by using quotation marks and by providing a clearreference to the paper immediately after the quotation. If you are building on someone elsescode (e.g. our code from the classes, open-source projects, etc.), please make it clear whichaspects of the code are your work through the use of comments. The University has detailedadvice about academic integrity, and submissions that demonstrate a lack of that integritywill be treated under appropriate disciplinary procedures. How the Work will be MarkedMarking will take into account: background research and how you have used it to contextualise your work the choice of task environment and how you have used it/adapted it for your specificproject the effective use of artificial intelligence and agent-based systems ideas from thecourse and your wider studies in designing your autonomous agents how clear your question(s) are, how well the experiments have been designed toanswer them, and your level of rigour in planning and analysing the experiments how well the report answers the Question by using the evidence from the experiments the overall clarity and structure of the report, appropriate use of scientific andtechnical English, and the quality of charts, diagrams, pseudocode where relevant the quality of reflection on the successes and limitations of the work (for students doing a presentation) the structure of the presentation, the clarity ofexplanations, and good use of slides or other visual aidsCOMP3004 Marking SchemeEach of the following descriptors gives a broad idea of the achievement expected for a markin that range. Clearly, individual projects may fall short in some areas and show excellencein others. The marking should also be adjusted to reflect the intrinsic difficultly of the project. Band Guidelines90-100 Marks in this range are reserved for a superb all-round performance. Work done inall aspects of the project go beyond even high expectations. The student hasshown a thorough understanding of the problem. All expected tasks have beensuccessfully completed, the project shows depth and engagement with researchideas, and everything has been completed to a high standard. The report couldform the basis of a publishable conference/workshop paper. 80-89 Excellent contributions to all areas of the project. Exceeded expectations in someareas. Demonstrates knowledge and understanding of the project that is beyondstandard resources covered in the module. Clear appreciation of the project as awhole, its adequacies, limitations and possibilities for future development. Theproject demonstrates insight and depth beyond that usually expected inundergraduate work. 70-79 Very good contributions to all areas of the project. Successful completion of theproject tasks. Demonstrated initiative and creative problem-solving ability. Able toundertake the work in a competent and independent manner. Able to reflectaccurately on adequacy and limitations of the projects achievements. 60-69 Good appreciation of background. A good attempt at applying this to the task, withdemonstrated ability to cope with difficulties. Good technical skills in several areas. Whilst most of the core aims of the project have been achieved, it might come alittle short in some areas. Good reflective understanding of the project. 50-59 Satisfactory background reading and a competent attempt at their tasks. Reasonable technical competence demonstrated. The core task completedsatisfactorily, but little achieved beyond that. Able to reflect satisfactorily on theproject. 40-49 Pass level. Competent background reading and appreciation of the project area. Basic technological competence. Some areas of the core tasks may beincomplete, but a decent attempt has been made at them. Able to reflect in alimited way on the project. 30-39 Unsatisfactory. Some attempt has been made at the background reading butclearly only partial understanding of project topic. Incomplete attempt at the coretasks. Weak technical competence. Little ability to reflect adequately on theproject. 20-29 Inadequate background reading, but shows some limited understanding of howideas can be linked to the task. Minimal attempt at the core tasks, showing poorunderstanding. A substantial amount of work is still needed to achieve the coretasks. Minimal reflection on the project. 10-19 Minimal attempt at background reading, inappropriate use of material, almost noattempt at core tasks. Very poor understanding of the problem. Minimal or noreflection on the project. 0-9 No or almost no significant attempt.COMP4105 Marking SchemesEach of the following descriptors gives a broad idea of the achievement expected for a markin that range. Clearly, individual projects may fall short in some areas and show excellencein others. The marking should also be adjusted to reflect the intrinsic difficulty of the project. Presentation COMP4105Band Guidelines9-10 A professional-level presentation of exceptional clarity and very clear structure, with very high-quality slides or other visual aids that flow seamlessly with thespoken presentation7-8 A clearly structured presentation, which explains all aspects of the project well, andwhich has high-quality slides or other visual aids that are tied in strongly with thespoken presentation5-6 Pass level. A competent Presentation that has a decent structure, gives acompetent description of most aspects of the project, and where the slides andother visual aids are largely clear and related to the spoken presentation3-4 A presentation that has some level of organisation but where the topics are notpresented in a clear order or where the presentation jumps from topic-to-topic, some explanations not clear, visual aids provided but not very clear and/or not veryrelated to the spoken presentation1-2 A presentation that mentions some aspects of the project work but is largelydisorganised to the point where it cannot be followed and where most explanationsare unclear, and where visual aids are unclear and/or not related to the spokenpresentation0 No significant attempt at presentationReview report COMP4105Band Guidelines90-100 A professional-level review of the literature/technology, demonstrating a clear anddeeply analytical/critical understanding of relevant work, an original structure to thereview, insightful links between the various papers and technologies reviewedleading to an innovative thematic analysis, and a very clear link to the project work. 80-89 A clear and deeply analytical/critical understanding of relevant work, an insightfulstructure to the review, a clear thematic understanding making links between thevarious papers and technologies clear, and a very clear link to the project work. 70-79 A clear and analytical/critical understanding of relevant work, a structure to thereview, links between the various papers and technologies brought out, and a clearlink to the project work. 60-69 A clear understanding of relevant work with some analysis/critique, some structureto the review, some thematic links between papers and technologies identified, and connected in parts to the project work. 50-59 Pass level. A competent understanding of relevant work with some attempt atanalysis/critique in parts, some Structure to the review, occasional attempts tomake thematic links between papers and technologies, and broadly related to theproject work. 40-49 Understanding of some relevant work but incomplete/misunderstood in parts, withlittle analysis/critique, largely unstructured, not many links betweenpapers/technologies, link with project not very clear30-39 Some papers/technologies have been studied and there is some understanding, but much is incomplete/misunderstood/irrelevant, no meaningful analysis/critique, papers/technologies presented independently, link with project not very clear20-29 A few papers/technologies have been looked at, but understanding is low andthere is no analysis/critique, no links between items studied, minimal structure,little link with project. 10-19 A couple of paper/technologies have been mentioned, but with very littleunderstanding, no links between them or structure, and not clear how they relate tothe project0-9 No or almost no significant attempt.Project work COMP4105Band Guidelines90-100 Marks in this range are reserved for a superb all-round performance. Work done inall aspects of the project go beyond even high expectations. The student hasshown a thorough understanding of the problem. All expected tasks have beensuccessfully completed, the project shows depth and engagement with researchideas, and everything has been completed to a high standard. The report couldform the basis of a publishable conference/workshop paper. 80-89 Excellent contributions to all areas of the project. Exceeded expectations in someareas. Demonstrates knowledge and understanding of the project that is beyondstandard resources covered in the module. Clear appreciation of the project as awhole, its adequacies, limitations and possibilities for future development. Theproject demonstrates insight and depth beyond that usually expected inundergraduate work. 70-79 Very good contributions to all areas of the project. Successful completion of theproject tasks. Demonstrated initiative and creative problem-solving ability. Able toundertake the work in a competent and independent manner. Able to reflectaccurately on adequacy and limitations of the projects achievements. 60-69 Good appreciation of background. A good attempt at applying this to the task, withdemonstrated ability to cope with difficulties. Good technical skills in several areas. Whilst most of the core aims of the project have been achieved, it might come alittle short in some areas. Satisfactory or good reflective understanding of theproject50-59 Pass level. Competent background reading and appreciation of the project area. Basic technological competence. Some areas of the core tasks may beincomplete, but a decent attempt has been made at them. Able to reflect in alimited way on the project. 40-49 Unsatisfactory. Some attempt has been made at the background reading butclearly only partial Understanding of project topic. Incomplete attempt at the coretasks. Weak technical competence. Little ability to reflect adequately on theproject. 30-39 An attempt has been made at the background reading but clearly only partialunderstanding of project topic. Attempt at the core tasks, but not much achievedoverall. Weak technical competence. Minimal reflection on the project. 20-29 Inadequate background reading, but shows some limited understanding of howideas can be linked to the task. Minimal attempt at the core tasks, showing poorunderstanding. A substantial amount of work is still needed to achieve the coretasks. Minimal reflection on the project. 10-19 Minimal attempt at background reading, inappropriate use of material, almost noattempt at core tasks. Very poor Understanding of the problem. Minimal or noreflection on the project. 0-9 No or almost no significant attempt.请加QQ：99515681 或邮箱：99515681@qq.com WX：codehelp

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