JUNTA ADMINISTRATIVA DEL REGISTRO NACIONAL REGISTRO DE LA PROPIEDAD INDUSTRIAL

During the Expert FPS Gameplay Study, all 4 participants had opinions on the performance and behaviour of the AI. The following list of remarks was extracted from each of the participant‟s transcripts and is described here with reference to the situation occurring during their game play. It should be noted that participants 1 and 2 had considerably less remarks about the performance of the bot as they were both performing the Talk-out-Loud method and were only required to talk about what they were doing while playing.

Table 4.9 - Expert FPS Gameplay Study Participant Remarks

Participant Comment

Code

Remark Game Play Context

1.1 “...inUT run directly towards your movement where they are locked on at point blank range. Makes it very hard to shoot them”

Participant engaged bot and found the bot‟s ability to lock on, track and run towards them unsettling

1.2 “And he walked into my green slime. Try not to say anything particularly … bad there”

Bot unexpectedly walked into the ordnance placed by the participant 1.3 “You just spawned, you

shouldn‟t be armed”

Participant found the bot‟s ability to be armed so readily after re- spawning surprising

2.1 “Don‟t want to let her get line of sight with that gun because

Participant avoiding being in view of the bot when it is using a Current occurrence in game Affects perceived threat level Affects willingness to change behaviour Affects priority of behaviours

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she is very good with it” particular weapon 3.1 “...and if they were a human

player they may have thought they may ignore him and try and get the armour or more ammo or whatever before they try to engage me”

Opinion of how a human player behaves after a kill concerning a nearby re-spawning player

3.2 “I mean a few times it shot me and it‟s just gone back on its patrol path and I hadn‟t realized where it was”

Bot is aggressive but non- committed to finishing off and hunting down the participant 3.3 “It seemed realistic enough,

like a human player it seemed to keeping to trends”

Participant‟s opinion of the bot‟s patrol path

3.4 “I was always of the opinion that the bot was a better player than I was so I wanted to keep my health”

Participant‟s reasoning behind focusing on picking up health packs

3.5 “I did, yeah. I was pretty much always scared of the bot”

Participant‟s opinion concerning the bot‟s advantage over them concerning weapons and armour 3.6 “As for the biorifle I felt that

she hated it as much as I did” Participant‟s observation concerning bots usage of certain weapons

3.7 “See this was the sort of situation which I did not want to get into. She can spin faster and you can see I just lost her there”

Close combat, frenzied engagement where participant could not focus on bot but the bot could focus on the participant

4.1 “Which would be good to see in AI. They probably do it, I dunno”

Participant‟s opinion of a bot engaging in close combat with a flak cannon

4.2 “Once they got a weapon they stuck with it”

Participant‟s observation about the bot‟s choice of weapon

4.3 “I had much better map control

then the AI” Participant‟s opinion regarding the level of control they had over the map

4.4 “See I put it down to the bot's incompetence”

Participant‟s opinion regarding map control and priority of pickups 4.5 “They foolishly come around

the corners with the flak cannon. It's like pretty much a given”

Observation that the bot blindly charges into ambushes resulting in easy kills

4.6 “Yeah like here I'm never gonna win this engagement they have a minigun, I have a minigun and I'm shooting up at them because they got better cover, they got better

Participant‟s assessment and opinion of result of a current engagement with the bot

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everything”

4.7 “I know that they do have weapons they prefer but I didn't really get the feeling that this bot had a weapon they preferred”

Participant‟s observation about the bot‟s choice of weapon

4.8 “Like so they are inherently a little bit rubbish. Like they give themselves another 15 seconds before they go after it”

Participant‟s assessment of the bot‟s reaction to newly spawned pickups and their transition to going after them

Many of these observations can be linked back to the original decision making process made by the bots. For example, observations 1.2, 3.1, 3.2 and 4.5 from Table 4.9 refer to bot decision making which is deemed illogical by the participants. This can work both for and against the AI in terms of predictability. For instance, several of the participants commented on the bots behaviour concerning the picking up of items and armour. The term „patrol path‟ can be used to describe this activity and for several of the participants, the bot was seen to either arm up unexpectedly faster than anticipated or fall short compared to the human player. There were also cases of the bot doing what seemed like illogical actions, continuing to pick up items instead of engaging the player. While many of the observations derive from what may initially be perceived as a mechanical process (e.g. aiming, navigating), it seems it is not so much the action itself that throws the player off as it is the choice of the action at the particular time. To use an instance from the examples, in the case of comment 4.5, the participant commented on a bot‟s recklessness in walking into ambushes coming off as non-player-like, resulting in exploitable and easy kills. In comparison, a human player would typically exhibit hesitation or caution with their current and future actions, thus possibly avoiding the ambush entirely.

The previous list of comments can also be compared to the comments made by participants of a previous study that examined player interactions with bot AI (Conroy & Wyeth, 2010). These comments can be seen in Table 4.10 and are extracted from an open-ended questionnaire question related to the participant‟s performance and observations. Although this study was performed using the game Quake III: Arena by ID Games and was run to test for different aspects of AI under different circumstances, similar observations can be made with the game‟s AI.

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Table 4.10 - Honours Study Participant Observations

Participant ID

Comment

1 “The only issue was that they turn very quick when you shoot them or sometimes they shoot

at you when they have no reason to”

2 “I think the biggest factor is reaction speed and accuracy – if they have excellent accuracy

and reaction time you‟re screwed”

3 “I felt their environmental awareness and weapon usage were fairly human-like, but I felt

their tracking and accuracy was slightly too good, and their movements in combat were a bit too robotic and precise”

4 “…even fewer duck in and out of cover like I would.”

“If bots had a preference to try to get the better armour and best weapons that would add to their difficulty”

5 “Humans would mix up their movements more esp with jumps”

“I noticed that the bots didn‟t change up their movement”

6 “They are able to tell where you are if you attempt to sneak up on them” 7 “…a few of the shots they did were a bit „far out‟”

“Also their navigation around the map seemed a little too spot on.”

9 “Weapon usage wasn‟t very good …”

“Bots were often nowhere to be found, movement wasn‟t anything like people”

11 “Bots were quite easy, they lacked afterthought”

“Also they lose focus on players. Bots seem to congregate in a specific area making them easier to kill”

14 “AI seemed to play in on steady skill level the whole game – not adapting or fluctuating in

skill or tactic so it became easier to predict them thus killing them more often.”

15 “I did notice the AI making use of an area with good line of sight and nearby health. This

use of tactic is something you can expect from experienced players”

18 “... the Ai was barely aware of me at times allowing me to sneak past, but whenever entering

a large group was quickly annihilated”

There are obvious similarities in the data, especially those concerning the non- player-like behaviour of the bots. While the majority of the concerns from this study were to do with the mechanical execution of actions such as aiming, moving and reactions (e.g. participants 3, 9, 18), it is also possible to observe many of the non- player-like decisions made by bots from this data.