function recalculateTarget() { //this is all our example logic
var candidate_ball = null; //first we don't have candidate to eat
var candidate_distance = 0;
var my_ball = client.balls[ client.my_balls[0] ]; //we get our first ball. We don't care if there more then one, its just example.
if(!my_ball) return; //if our ball not spawned yet then we abort. We will come back here in 100ms later
for(var ball_id in client.balls) { //we go through all balls we know about
var ball = client.balls[ball_id];
if(ball.virus) continue; //if ball is a virus (green non edible thing) then we skip it
if(!ball.visible) continue; //if ball is not on our screen (field of view) then we skip it
if(ball.mine) continue; //if ball is our ball - then we skip it
if(ball.isMyFriend()) continue; //this is my friend, ignore him (implemented by custom property)
if(ball.size/my_ball.size > 0.5) continue; //if ball is bigger than 50% of our size - then we skip it
var distance = getDistanceBetweenBalls(ball, my_ball); //we calculate distances between our ball and candidate
if(candidate_ball && distance > candidate_distance) continue; //if we do have some candidate and distance to it smaller, than distance to this ball, we skip it
candidate_ball = ball; //we found new candidate and we record him
candidate_distance = getDistanceBetweenBalls(ball, my_ball); //we record distance to him to compare it with other balls
}
if(!candidate_ball) return; //if we didn't find any candidate, we abort. We will come back here in 100ms later
client.log('closest ' + candidate_ball + ', distance ' + candidate_distance);
client.moveTo(candidate_ball.x, candidate_ball.y); //we send move command to move to food's coordinates
}
const onTick = () => {
if (roundsToSkip > 0) {
roundsToSkip -= 1;
return;
}
const startTime = Date.now();
const state = getCurrentState();
if (!_.isObject(state)) {
if (_.isNumber(prevScore)) {
console.log("---------------Dead, reward: " + (-prevScore) + "--------------");
agent.learn(-prevScore);
//clear experience
agent.exp = []; // experience
agent.expi = 0; // where to insert
agent.t = 0;
}
prevScore = null;
return;
}
const reward = _.isNumber(prevScore) ? state.score - prevScore : null;
if (_.isNumber(reward)) {
//agent.learn(reward);
}
const velocity = _.isObject(prevPos) ? new Vec(state.me.pAvg.x - prevPos.x, state.me.pAvg.y - prevPos.x) : new Vec(0,0);
const prevPos = state.me.pAvg;
let action;
let xPot = 0;
let yPot = 0;
_.forEach(state.sensorDetections, (sd, i) => {
const s = sensors[i].normalizeClone();
if (sd.targetType === targetTypes.CELL) {
if (sd.targetSize < state.me.size) {
xPot += sd.targetSize/(sd.dist * sd.dist) * s.x;
yPot += sd.targetSize/(sd.dist * sd.dist) * s.y;
} else {
xPot -= sd.targetSize/(sd.dist * sd.dist) * s.x;
yPot -= sd.targetSize/(sd.dist * sd.dist) * s.y;
}
} else if (sd.targetType === targetTypes.VIRUS && sd.targetSize + 50 < state.me.totalSize && state.me.totalBalls === 1) {
xPot -= sd.targetSize/(sd.dist * sd.dist) * s.x;
yPot -= sd.targetSize/(sd.dist * sd.dist) * s.y;
}
});
let wDist = state.me.pAvg.x - map.minX;
if (wDist < 500) {
xPot -= 5/(wDist * wDist);
}
wDist = map.maxX - state.me.pAvg.x;
if (wDist < 500) {
xPot += 5/(wDist * wDist);
}
wDist = state.me.pAvg.y - map.minY;
if (wDist < 500) {
yPot -= 5/(wDist * wDist);
}
wDist = map.maxY - state.me.pAvg.y;
if (wDist < 500) {
yPot += 30/(wDist * wDist);
}
if (Math.abs(xPot) > Math.abs(yPot)) {
if (xPot > 0) {
action = actionTypes.LEFT;
} else {
action = actionTypes.RIGHT;
}
} else {
if (yPot > 0) {
action = actionTypes.DOWN;
} else {
action = actionTypes.UP;
}
}
let moveTo;
if (Math.abs(xPot) < 0.0001 && Math.abs(yPot) < 0.0001) {
roundsToSkip = 10;
action = 3 - Math.floor(Math.random() * 4);
}
if (Math.random() > prob) {
action = 3 - Math.floor(Math.random() * 4);
roundsToSkip = 0;
}
//const action = agent.act(serialize(state, velocity));
if (action === actionTypes.UP) {
moveTo = new Vec(state.me.pAvg.x, state.me.pAvg.y + 500);
} else if (action === actionTypes.RIGHT) {
moveTo = new Vec(state.me.pAvg.x + 500, state.me.pAvg.y);
} else if (action === actionTypes.DOWN) {
moveTo = new Vec(state.me.pAvg.x, state.me.pAvg.y - 500);
} else if (action === actionTypes.LEFT) {
moveTo = new Vec(state.me.pAvg.x - 500, state.me.pAvg.y);
}
client.moveTo(moveTo.x, moveTo.y);
const closest = _.min(state.sensorDetections, (sd) => sd.dist);
console.log({
action: action,
reward: reward,
time: Date.now() - startTime,
dist: closest.dist
});
prevScore = state.score;
};