## +23 ### BehaviorTree.CPP: Task Planning for Robots and Virtual Agents ## DAVIDE FACONTI ## 20 23 October 01 - 06 ## What you will learn today 1. What Behavior Trees are 2. About the C++ library ments/8/d/b/6/8db662e9d441565a9dd326035c73ae34/p7_1.jpg) ## Robot Behaviors This Coordinator or Task Planner is also the highest level of abstraction of our system, where we focus on WHAT the robot does

## +24 ## Work Contracts Rethinking Task Based Concurrency and Parallelism for Low Latency C++ MICHAEL A MANISCALCO ### “We cannot solve our problems with the same thinking we used when we created them So what is there to Rethink? ## Rethinking: Task Queues  ## Problem #1 - Task Queues Do Not Scale Well: • Contention: ☐ problems: ☐ Task starvation ☐ Load balancing ☐ Forfeits strict FIFO behaviour ○ Increases memory footprint (or requires allocations) ☐ Terrible task selection "fairness" ## Rethinking: Task Queues

## +23 ## Taro: Task graph-based Asynchronous Programming Using C++ Coroutine DIAN-LUN LIN 20 23 October 01 - 06 ## Agenda • Understand the motivation behind Taro • Learn to use the Taro C++ programming application • Conclusion ## What is Task Graph-based Programming System (TGPS) • TGPS encapsulates function calls and their dependencies in a top-down task graph ## What is Task Graph-based Programming System function calls and their dependencies in a top-down task graph  ## What is Task Graph-based Programming System (TGPS) • TGPS encapsulates

the current stable version of Celery (4.0). For development docs, go here. ## Celery - Distributed Task Queue Celery is a simple, flexible, and reliable distributed system to process vast amounts of messages operations with the tools required to maintain such a system. It’s a task queue with focus on real-time processing, while also supporting task scheduling. Celery has a large and diverse community of users and Getting Started Release: 4.0 Date: Dec 09, 2016 • Introduction to Celery. • What's a Task Queue? • What do I need? • Get Started • Celery is... • Features • Framework

## Celery - Distributed Task Queue Contents: • Getting Started • Introduction • Broker Installation • First steps with Celery • First steps with Django • Periodic Tasks Configuration and defaults • Example configuration file • Concurrency settings • Task result backend settings • Database backend settings • AMQP backend settings • Cache • MongoDB backend settings • Messaging settings • Task execution settings • Worker: celeryd • Periodic Task Server: celerybeat • Monitor Server: celerymon • Cookbook

pages 38 1.12 Architecture 41 1.13 Examples 43 Python Module Index Django Q is a native Django task queue, scheduler and worker application using Python multiprocessing. ## Features • Multiprocessing queue name. Defaults to 'default'. Note: Tasks are encrypted. When a worker encounters a task it can not decrypt, it will be discarded or failed. #### 1.2.2 workers The number of workers to basis. Defaults to 500. #### 1.2.4 timeout The number of seconds a worker is allowed to spend on a task before it’s terminated. Defaults to None, meaning it will never time out. Set this to something that

Monitor 21 1.7 Admin pages 24 1.8 Examples 26 Python Module Index 31 Django Q is a native Django task queue, scheduler and worker application using Python multiprocessing. ## Features • Multiprocessing several projects using the same Redis server. Note: Tasks are encrypted. When a worker encounters a task it can not decrypt, it will be discarded. #### 1.2.2 workers The number of workers to use in the basis. Defaults to 500. #### 1.2.4 timeout The number of seconds a worker is allowed to spend on a task before it’s terminated. Defaults to None, meaning it will never time out. Set this to something that

http://github.com/ask/celery/ Keywords task queue, job queue, asynchronous, rabbitmq, amqp, redis, Django, Python, Webhooks, queue, distributed Celery is a task queue/job queue based on distributed message workload. The result of the task can be stored for later retrieval (called its “tombstone”). #### 1.1.2 Example You probably want to see some code by now, so here’s an example task adding two numbers: from from celery.decorators import task @task def add(x, y): return x + y You can execute the task in the background, or wait for it to finish: >>> result = add.delay(4, 4) >>> result

older version of Celery (2.2). For the latest stable version please go here. ## Celery - Distributed Task Queue Contents: • Getting Started • Introduction • Broker Installation • First X • First steps with Celery • Creating a simple task • Configuration • Running the celery worker server • Executing the task • Where to go from here • Resources • Getting http://github.com/ask/celery/ Keywords: task queue, job queue, asynchronous, rabbitmq, amqp, redis, python, webhooks, queue, distributed Celery is an open source asynchronous task queue/job queue based on distributed

192 10.4 celery.task ..... 192 10.5 celery.task.base ..... 193 10.6 celery.task.sets ..... 201 10.7 celery.result ..... 202 10.8 celery.task ..... 205 10.9 celery.task.control ..... 207 10.10 celery.task.http ..... 209 10.11 celery.schedules ..... 211 10.12 celery.signals ..... 212 10.13 celery.exceptions ..... 217 10.14 celery.loaders ..... 217 10.15 celery.loaders.app .. .. 241 11.1 Celery Deprecation Timeline ..... 241 11.2 Internals: The worker ..... 241 11.3 Task Message Protocol ..... 243 11.4 “The Big Instance” Refactor ..... 244 11.5 Internal Module Reference