In practice, when we are training the Q-learner, we do not always pick the action that has the maximum Q-value as the next move during the self-play phase. The Q represents the “quality” of some move given a specific state the following pseudo-code outlines the algorithm:
The simplest way to use an agent trained from Q-learning is to pick the action that has the maximum Q-value.
Here, our neural network acts as a function approximator for a function Q, where Q(state, action) returns a long-term value of the action given the current state. Perhaps the most common technical approach is Q-learning. The typical setup involves an environment, an agent, states, and rewards.
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The learning agent learns by interacting with the environment and then figures out how to best map states to actions. There are various technical approaches to deep reinforcement learning, where the idea is to learn a policy that maximizes long-term reward represented numerically. Our experiments focused on how to use the data collected from human players to refine the agent’s ability to play (and win!) against human players. Over time, the automated Battleship-playing agent did better and better, developing strategies to improve its play from game to game.Ĭurrent progress has been made to establish a framework for (1) playing Battleship from random (or user-defined) ship placement (2) deep reinforcement learning from a Deep Q-learner trained from self-play on games starting from randomly positioned ships and (3) collecting data from two-player Battleship games.
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Ten years after that initial release, Milton Bradley released a computerized version, and now there are numerous online versions that you can play and open source versions that you can download and run yourself.Īt GA-CCRi, we recently built on an open source version to train deep learning neural networks with data from GA-CCRi employees playing Battleship against each other. Participants may access the building or ship only after that time.According to the Wikipedia page for the game Battleship, the Milton Bradley board game has been around since 1967, but it has roots in games dating back to the early 20th century. The Nauticus building, Hampton Roads Naval Museum, and the battleship do not open until 10:00 a.m. For clothing concerns or event set-up/take-down requirements, please call us in advance to make arrangements.ġ1. Those individuals that do not comply will not be allowed to attend the ceremony. Navy instructions, working uniforms and civilian clothes are prohibited. Active duty guests must wear the correct uniform IAW current U.S. The ceremony participants are responsible for setup and take down immediately before and after the ceremony.ġ0.
Equipment, podium, and chairs are made available by the museum. Paid parking is available at the Plume Street parking garage across the street from the battleship.ĩ. The Hampton Roads Naval Museum cannot validate parking. No food, drinks, candy, or tobacco products are allowed on board the ship or the Museum. In the case of inclement weather, the participants are responsible for an alternate location.ħ. There are no facilities inside the Hampton Roads Naval Museum available. Before boarding the battleship, report to the Hampton Roads Naval Museum on the second floor and check in at the desk.Ħ. If you cancel your event notify us immediately so someone else can have your spot.ĥ. The phone number for the Military Ceremonies Coordinator is (757) 322-3106.Ĥ. Please contact us three days prior to your event to make sure everything is on track for your ceremony. Ceremonies are held only on Wednesdays, Thursdays and Fridays from 10:00 a.m. Ceremony attendees may wear a mask and follow best practices for social distancing.Ģ. The Commonwealth of Virginia has lifted the mask mandate for vaccinated individuals as well as the restrictions and social distancing requirements on outdoor gatherings.ġ. Please read the information below before planning a safe and successful ceremony with the Hampton Roads Naval Museum.
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