CSCI3180 – Principles of Programming Languages – Spring 2019 Assignment 2 — Your First Date with Python and Duck Typing Deadline: Mar 10, 2019 (Sunday) 23:59 1 Introduction The purpose of this assignment is to offer you the first experience with Python, which supports the object-oriented programming paradigm. Our main focuses are Dynamic Typing and […]
第十届中国大学生服务外包创新创业大赛 企业命题类赛题手册 中国大学生服务外包创新创业大赛组委会 2019年2月 中国大学生服务外包创新创业大赛组委会 目录 一、 概述………………………………………………… 2 二、 企业赛题…………………………………………….. 4 2.1 【A01】2018 网络零售平台商品分类【浪潮】 …………………………… 4 2.2 【A02】基于华云 chinac 公有云平台，设计云监控管理系统【华云】 …………. 6 2.3 【A03】大规模资金流入流出的大数据预测【阿里创新创业中心】……………. 9 2.4 【A04】语音人机交互技术带来的家庭娱乐体验升级【阿里人工智能实验室】 ….. 16 2.5 【A05】基于 PaddlePaddle 的校园生活服务类产品【百度】 ……………….. 19 2.6 【A06】智能网联汽车驾驶健康伙伴系统【东软睿道】……………………. 22 2.7 【A07】智能化跨境商品交易平台【东软睿道】…………………………. 26 2.8 【A08】智能会议室管理系统【虹软】………………………………… 30 2.9 【A09】智慧教室学生状态检测系统【慧科集团】……………………….. 34 2.10 【A10】运用数据分析和可视化技术创造完美的数据大屏交互体验【融创软通】 .. 37 2.11 【A11】基于微信的移动智能学习平台【文思海辉】…………………….. 41
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Blending: An ACT-R Mechanism for Aggregate Retrievals Christian Lebiere Psychology Department Carnegie Mellon University Pittsburgh, PA 15213 http://act.psy.cmu.edu Plan • Background • Basic mechanism • Spectrum of applicability • Application: similarity judgment • Application: magnitude estimate • Details • Activation • Related IA mechanisms • Conclusions Background • Goal: “ACT-R doesn’t have a mechanism for
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Artificial Intelligence – Assessed Exercise (deadline: March 16, 5pm UK time) (Workload: ∼ 20 hours, it should not take you much more than that !!!) 1 Problem Statement (Python Programming + Short Report) Your task is to design, implement, evaluate and document three virtual agents which are (potentially) able to reach a goal in a
Department of Electrical & Computer Engineering University of California, Davis EEC 170 – Computer Architecture Winter Quarter 2019 Laboratory Exercise 2: RISC-V Computer Arithmetic Due Date: Feb 15, 2019 Full Points 150 Objectives The objectives of this exercise are four fold. a) You will learn how RISC-V assembly programming, especially the use of shift and
pacmanAgents.py (original) # pacmanAgents.py # ————— # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # For more
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graphicsDisplay.py (original) # graphicsDisplay.py # —————— # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # For more
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layout.py (original) # layout.py # ——— # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # For more
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graphicsUtils.py (original) # graphicsUtils.py # —————- # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # For more
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pacman.py (original) # pacman.py # ——— # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # For more
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