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Stories and insights from the team behind HASH

Improving the Prisoners Dilemma with Q-Learning

We recently published HASH’s Q-Learning Library, to make it easier to start building simulations and agents that use reinforcement learning. Let’s take a look at how we can use the library to update an older simulation. We’ll take the classic Prisoner’s Dilemma simulation and add an agent which uses q-learning to determine its strategy. The […]

Reinforcement Learning in HASH Simulations

Q-Learning Map Explorer Reinforcement Learning (RL) is a way to teach an agent how to behave in an environment by rewarding it when it does well and penalizing it when it does poorly. Using RL in HASH, you can create complex agents that figure out ‘on their own’ optimal strategies to follow in a simulation. […]

Physics in HASH

We recently released the HASH Physics Library, which provides behaviors that can help you start creating physics simulations in HASH. The library is written in Rust, which means that it’s optimized to run in our engine. The HASH docs contain more information about each of the behaviors. You can add the physics library to your […]

Surviving a Chip Shortage

The COVID-19 pandemic has been a source of exogenous shocks to supply and demand in many industries across the market. One specific market currently experiencing shortages is the semiconductor industry. This has far-reaching consequences, because “chips” have become ubiquitous as raw components for many different industries The auto and consumer electronics industry are both experiencing […]

Top 10 Datasets: June 2021

HASH’s Index includes a large collection of user-uploaded datasets you can use to generate and power a simulation. Below are some of our favorite datasets:  Master List of LEGO Part Numbers: Master List of Official LEGO™ parts/numbers. Thousands of legos with descriptions of the parts. Provider: Peeron. SARS-CoV-2 Superspreading Events: A dataset with 1,100 SSEs […]

Discrete Event Library

Discrete event modeling is a popular paradigm for building simulations, introducing “events” that cause changes in the simulation state. In between events, no changes happen to the state. This saves computational effort and reduces the time to compute a simulation. You can imagine a simulation of a manufacturing process where a new car rolls off […]

Calibrating Models of Cell Replication

Agent-based models provide an alternative way of exploring and explaining the world. In this paper, researchers constructed a mathematical model to explain the partial synchronicity that occurs in the replication of cell samples. The growth of a sample of cells is exponential, but discrete. Because of this, if a sample of cells is completely synchronous […]

Generating a Simulation from Terraform

The Infrastructure-as-Code (IaC) movement has revolutionized the way cloud infrastructure is managed, enabling self-documenting, version-controlled provisioning and maintenance of systems and hardware. While sysadmins are very much still required, tooling and best practices for programmatically setting up large computing infrastructures have dramatically improved as DevOps has matured. In particular, planning tools like Terraform make it […]

Modeling with System Dynamics

System Dynamics models are a powerful tool for visualizing and modeling complex systems. They break down a model into abstract or concrete quantities (stocks), and the rates at which they change (flows). HASH’s System Dynamics library makes it easy to incorporate these types of models into your simulations. With the HASH library, models are always […]

Optimization Experiments

Often, the goal of creating simulations is to find the optimal combination of policies or parameters for achieving some objective: e.g. to maximize revenues, minimize costs, improve the efficacy of an advertising campaign, or boost throughput in a factory. While HASH makes it easy for you to modify parameters and explore your simulation, once the […]